Staff Data Engineer

Posted 4 months agoViewed

View full description

💎 Seniority level: Staff, 10+ years

📍 Location: United States

💸 Salary: 131414.0 - 197100.0 USD per year

🔍 Industry: Mental healthcare

🏢 Company: Headspace👥 11-50 Wellness Health Care Child Care

⏳ Experience: 10+ years

🪄 Skills: SQLCloud ComputingETLSnowflakeData engineeringData modelingData analytics

Requirements:

10+ years of success in enterprise data solutions and high-impact initiatives.
Expertise in platforms like Databricks, Snowflake, dbt, and Redshift.
Experience designing and optimizing real-time and batch ETL pipelines.
Demonstrated leadership and mentorship abilities in engineering.
Strong collaboration skills with product and analytics stakeholders.
Bachelor’s or advanced degree in Computer Science, Engineering, or a related field.

Responsibilities:

Drive the architecture and implementation of pySpark data pipelines.
Create and enforce design patterns in code and schema.
Design and lead secure and compliant data warehousing platforms.
Partner with analytics and product leaders for actionable insights.
Mentor team members on dbt architecture and foster a data-first culture.
Act as a thought leader on data strategy and cross-functional roadmaps.

Apply

Related Jobs

Apply

🔥 Staff Data Engineer

Posted 3 days ago

📍 United States

🧭 Full-Time

💸 160000.0 - 230000.0 USD per year

🔍 Daily Fantasy Sports

🏢 Company: PrizePicks👥 101-250💰 Corporate about 2 years agoGaming Fantasy Sports Sports

🔧 Requirements

7+ years of experience in a data Engineering, or data-oriented software engineering role creating and pushing end-to-end data engineering pipelines.
3+ years of experience acting as technical lead and providing mentorship and feedback to junior engineers.
Extensive experience building and optimizing cloud-based data streaming pipelines and infrastructure.
Extensive experience exposing real-time predictive model outputs to production-grade systems leveraging large-scale distributed data processing and model training.
Experience in most of the following:
Excellent organizational, communication, presentation, and collaboration experience with organizational technical and non-technical teams
Graduate degree in Computer Science, Mathematics, Informatics, Information Systems or other quantitative field

💡 Responsibilities

Enhance the capabilities of our existing Core Data Platform and develop new integrations with both internal and external APIs within the Data organization.
Develop and maintain advanced data pipelines and transformation logic using Python and Go, ensuring efficient and reliable data processing.
Collaborate with Data Scientists and Data Science Engineers to support the needs of advanced ML development.
Collaborate with Analytics Engineers to enhance data transformation processes, streamline CI/CD pipelines, and optimize team collaboration workflows Using DBT.
Work closely with DevOps and Infrastructure teams to ensure the maturity and success of the Core Data platform.
Guide teams in implementing and maintaining comprehensive monitoring, alerting, and documentation practices, and coordinate with Engineering teams to ensure continuous feature availability.
Design and implement Infrastructure as Code (IaC) solutions to automate and streamline data infrastructure deployment, ensuring scalable, consistent configurations aligned with data engineering best practices.
Build and maintain CI/CD pipelines to automate the deployment of data solutions, ensuring robust testing, seamless integration, and adherence to best practices in version control, automation, and quality assurance.
Experienced in designing and automating data governance workflows and tool integrations across complex environments, ensuring data integrity and protection throughout the data lifecycle
Serve as a Staff Engineer within the broader PrizePicks technology organization by staying current with emerging technologies, implementing innovative solutions, and sharing knowledge and best practices with junior team members and collaborators.
Ensure code is thoroughly tested, effectively integrated, and efficiently deployed, in alignment with industry best practices for version control, automation, and quality assurance.
Mentor and support junior engineers by providing guidance, coaching and educational opportunities
Provide on-call support as part of a shared rotation between the Data and Analytics Engineering teams to maintain system reliability and respond to critical issues.

AWSBackend DevelopmentDockerLeadershipPythonSQLApache AirflowCloud ComputingETLGitKafkaKubernetesRabbitmqAlgorithmsApache KafkaData engineeringData StructuresGoPostgresSparkCommunication SkillsAnalytical SkillsCollaborationCI/CDProblem SolvingRESTful APIsMentoringLinuxDevOpsTerraformExcellent communication skillsStrong communication skillsData visualizationData modelingScriptingSoftware EngineeringData analyticsData management

Posted 3 days ago

Apply

🔥 Staff Data Engineer

Posted 15 days ago

📍 AL, AR, AZ, CA, CO, CT, FL, GA, ID, IL, IN, IA, KS, KY, MA, ME, MD, MI, MN, MO, MT, NC, NE, NJ, NM, NV, NY, OH, OK, OR, PA, SC, SD, TN, TX, UT, VT, VA, WA, WI

🧭 Full-Time

🔍 Insurance

🏢 Company: Kin Insurance

🔧 Requirements

7+ years of hands-on data engineering experience related to: Data structures and cloud platform environments and best practices (AWS strongly preferred, Azure, or GCP)
ETL performance tuning and cost optimization
Data lake and lakehouse patterns including open table formats (e.g. Iceberg, Hudi, Delta)
Proficiency in Python (Pandas, NumPy, etc.) and SQL for advanced data processing and querying
Experience influencing technical strategy, optimizing systems for scale, and reviewing team designs
Expertise in distributed data processing/storage (e.g., Apache Spark, Kafka, Hadoop, or similar)
Excellent communication skills and ability to explain complex concepts clearly and concisely
Detail-oriented with strong data intuition and a passion for data quality
Proven ability to model data and build production-ready ETL pipelines handling TBs of data.
Great time management and prioritization skills

💡 Responsibilities

Designing and developing scalable data pipelines and models for downstream analytics and reporting
Leading and collaborating with a cross-functional project team to implement data validation, QA standards, and effective data lifecycle management
Optimizing pipeline performance, cost, and data quality in a large-scale data environment
Migrating data warehouse (DBT, Redshift) architecture to Lakehouse (e.g: S3, Glue, Databricks, Unity catalog) architecture
Mentoring data engineers and promoting best practices in software engineering, documentation, and metadata management
Ensuring data security and compliance with regulations (e.g., GDPR, CCPA, GLBA) through robust pipeline design and access monitoring
Translating ambiguous business requirements into technical solutions using marketing domain knowledge

AWSPythonSQLCloud ComputingETLKafkaData engineeringData StructuresPandasMentoringTime ManagementExcellent communication skillsData visualizationData modelingData management

Posted 15 days ago

Apply

🔥 Member of Technical Staff, Data Engineer

Posted 18 days ago

📍 North America, Europe

💸 220000.0 - 270000.0 USD per year

🔍 AI Research

🏢 Company: Runway

🔧 Requirements

5+ years of industry experience in data engineering, analytics engineering, or similar roles
Strong proficiency in SQL and experience with modern data warehousing solutions (e.g., Snowflake, BigQuery, Redshift)
Experience designing and implementing ETL/ELT pipelines using tools like dbt, Airbyte, or similar.
Experience with Python or another programming language for data manipulation and automation
Knowledge of data privacy and data security best practices
Ability to translate business requirements into technical specifications and data models

💡 Responsibilities

Own the data pipeline, including the ingestion, storage, transformation, and serving of data
Build and optimize ETL processes to ensure data reliability, accuracy, and accessibility
Design, implement, and maintain a modern data warehouse architecture using industry best practices
Develop data models, tables, and views that empower teams to self-serve their analytics needs
Collaborate with ML Engineers, infrastructure engineers, and product managers to identify data requirements, build efficient data delivery systems, and create a unified data foundation that supports both technical innovation and business growth

AWSPostgreSQLPythonSQLCloud ComputingETLGCPSnowflakeAirflowAzureData engineeringData modelingData analytics

Posted 18 days ago

Apply

🔥 Staff Data Engineer - (Remote - US)

Posted 24 days ago

📍 United States

🧭 Full-Time

💸 160000.0 - 210000.0 USD per year

🔍 Software Development

🏢 Company: Jobgether👥 11-50💰 $1,493,585 Seed about 2 years agoInternet

🔧 Requirements

6–10 years of experience in data engineering, data analysis, or software development roles.
Proficient in SQL and NoSQL databases; strong hands-on experience with Spark/Databricks.
Skilled in modern data orchestration tools such as Airflow and cloud services like AWS (EC2, S3, Lambda, RDS, IAM).
Solid experience with web frameworks (Vue.js, React) and RESTful service development.
Familiarity with serverless architectures and messaging systems (SQS, SNS).
Bachelor’s degree in Computer Science or related discipline.
Demonstrated ability to manage complex codebases and deliver projects from design to deployment.

💡 Responsibilities

Design and implement scalable data pipelines to support integration across internal systems and third-party platforms.
Build and maintain data lake solutions using technologies such as Spark and Databricks.
Develop and manage cloud-based services and web applications to support data access and processing.
Ensure high data quality and availability standards across the enterprise.
Collaborate with engineering, analytics, and AI teams to understand data needs and deliver performant solutions.
Lead or contribute to architectural decisions and technical mentorship within the data team.
Implement DevOps and agile best practices across the development lifecycle.

AWSSQLCloud ComputingData AnalysisETLVue.JsAirflowData engineeringServerlessNosqlReactSparkRESTful APIsDevOps

Posted 24 days ago

Apply

🔥 Staff Data Engineer (Remote)

Posted about 1 month ago

📍 United States

🧭 Full-Time

🔍 Medical Technology

🏢 Company: external_career_site_usa

🔧 Requirements

7+ years of experience programming in SQL
5+ years programming in Snowflake
3+ years working with FiveTran
3+ years of experience in ETL/data movement including both batch and real-time data transmission using dbt
5+ years of experience data modeling including normalizing and dimensional modelling
5+ years of experience optimizing performance in ETL and reporting layers
3+ years of hands-on development and deployment experience with Azure cloud using .NET, T-SQL, Azure SQL, Azure Storage, Azure Data Factory, Cosmos DB, GitHub, Azure DevOps, and CI/CD pipelines
3+ years with APIs, microservices
3+ years of experience programming in Python/Java/C#

💡 Responsibilities

Build next generation distributed streaming and data pipelines and analytics data stores using streaming frameworks (Kafka, Spark Streaming etc.) using Programming languages like Python and ELT tools like Fivetran, DBT etc.
Perform unit tests and conduct reviews with other team members to make sure your code is rigorously designed, elegantly coded, and effectively tuned for performance.
Develop and deploy structured, semi-structured, and unstructured data storage models such as data lake and dimensional modeling
Evaluate and define functional requirements for data and analytical solutions
Monitor system performance, identify issues related to performance, scalability, and reliability, and design solutions to remediate
Partner with IT, Data Governance, and subject matter experts to create, automate, and deploy effective data quality monitors.
Develop and maintain enterprise data dictionary of data warehouse transformations and business rules
Ensure healthcare information security best practice controls are in place and they adhere to HIPAA utilizing a common control framework (i.e. NIST, HITRUST)
Implement master data management (MDM) solutions to collect, maintain, and leverage data for common business entities
Implement metadata management solutions to collection, maintain, and leverage application and system metadata

PythonSQLETLJavaKafkaSnowflakeC#TableauAzureData engineeringCI/CDRESTful APIsTerraformMicroservicesData visualizationData modeling

Posted about 1 month ago

Apply

🔥 Staff Data Engineer

Posted about 2 months ago

📍 United States

🧭 Full-Time

🔍 Healthcare

🏢 Company: Atropos Health👥 11-50💰 $33,000,000 over 1 year agoClinical Trials Medical Information Technology Health Care

🔧 Requirements

At least 5 years of experience working with messy real-world healthcare data (EHR data, claims) and experience with Real World Data / Evidence at least 3 years
Expertise working with common data models and terminology systems in healthcare data (data models and standards such as FHIR, OMOP, codesets like ICD 9/10, CPT, ATC, RxNorm, NDC, etc.)
Knowledge of common EHR and medical claim / administrative workflows and the basics of the US healthcare system (patient movement through a hospital or clinic, how medical procedures are reimbursed, etc.)
SQL (any dialect): at least 5 years, Python at least 4 years (Required)
Significant and deep experience as a data professional working with public cloud infrastructure to build data products (Required)
Knowledge of EHR data systems and at least 4 years of experience working intensively with EHR data in a data engineering and/or analytics environment
High level knowledge of ETL/ELT operations and data modeling

💡 Responsibilities

Create and maintain data pipelines to integrate, enrich, and map clinical, claims, and other data from multiple sources in the cloud
Design systems of data quality checks and assessments on clinical datasets
Expert knowledge of how to automate workflows and create reusable infrastructure in multiple public cloud environments (AWS, Azure, GCP)
Map data from one source into a common data model using many different frameworks, with a particular focus on PySpark and Spark SQL.
Create, maintain, tune, and document data flows in Databricks and Snowflake, Bigquery, and other diverse cloud tools
Filter, clean, transform, and integrate clinical data using your domain expertise of healthcare data and code systems and embedded knowledge
Work remotely with an interdisciplinary team and build and maintain strong relationships with research, clinical, product, and commercial stakeholders
Manage external customer, vendors, and customer relationships and create internal and external communications
Travel required to company or team offsites 3-4 weeks per year

AWSPythonSQLCloud ComputingETLSnowflakeData engineeringRDBMSSparkData modeling

Posted about 2 months ago

Apply

🔥 Staff Data Engineer

Posted 3 months ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: Life360👥 251-500💰 $33,038,258 Post-IPO Equity over 2 years ago🫂 Last layoff over 2 years agoAndroid Family Apps Mobile Apps Mobile

🔧 Requirements

Minimum 7 years of experience working with high volume data infrastructure.
Experience with Databricks and AWS.
Experience with dbt.
Experience with job orchestration tooling like Airflow.
Proficient programming in Python.
Proficient with SQL and the ability to optimize complex queries.
Proficient with large-scale data processing using Spark and/or Presto/Trino.
Proficient in data modeling and database design.
Experience with streaming data with a tool like Kinesis or Kafka.
Experience working with high volume event based data architecture like Amplitude and Braze.
Experience in modern development lifecycle including Agile methodology, CI/CD, automated deployments using Terraform, GitHub Actions, etc.
Knowledge and proficiency in the latest open source and data frameworks, modern data platform tech stacks and tools.
Always learning and staying up to speed with the fast moving data world.
You have good communication and collaboration skills and can work independently.
BS in Computer Science, Software Engineering, Mathematics, or equivalent experience.

💡 Responsibilities

Design, implement, and manage scalable data processing platforms used for real-time analytics and exploratory data analysis.
Manage our financial data from ingestion through ETL to storage and batch processing.
Automate, test and harden all data workflows.
Architect logical and physical data models to ensure the needs of the business are met.
Collaborate across the data teams, engineering, data science, and analytics, to understand their needs, while applying engineering best practices.
Architect and develop systems and algorithms for distributed real-time analytics and data processing.
Implement strategies for acquiring data to develop new insights.
Mentor junior engineers, imparting best practices and institutionalizing efficient processes to foster growth and innovation within the team.
Champion data engineering best practices and institutionalizing efficient processes to foster growth and innovation within the team.

AWSProject ManagementPythonSQLApache AirflowETLKafkaAlgorithmsData engineeringData StructuresREST APISparkCommunication SkillsAnalytical SkillsCollaborationCI/CDProblem SolvingAgile methodologiesMentoringTerraformData visualizationTechnical supportData modelingData analyticsData managementDebugging

Posted 3 months ago

Apply

🔥 Staff Data Engineer, Revenue & Growth Data

Posted 3 months ago

📍 US

🧭 Full-Time

💸 171400.0 - 260800.0 USD per year

🔍 Software Development

🏢 Company: Dropbox👥 1001-5000💰 $600,000,000 Debt Financing about 8 years ago🫂 Last layoff about 2 years agoPrivate Cloud Web Hosting File Sharing Enterprise Software Collaboration

🔧 Requirements

10+ years building large-scale data systems, with a demonstrated track record of technical leadership, including ownership of architectural direction and cross-team platform work
Proven ability to set architectural direction, lead platform evolution, and influence technical strategy across teams
Deep hands-on expertise with Spark, Spark SQL, and Databricks, along with experience orchestrating data pipelines using Apache Airflow, and writing performant, maintainable Python and SQL code
Track record of implementing data quality, testing, and observability systems at scale
Experience supporting monetization, financial, or product growth analytics with trusted and governed data models
Familiarity with cloud platforms (AWS, GCP, or Azure) and lakehouse paradigms (e.g., Delta Lake, Iceberg)

💡 Responsibilities

Architect the next-generation data platform for ARR, revenue attribution, and growth analytics — setting vision, driving alignment, and delivering at scale
Own and evolve core data models and systems used across Finance, Product, and Analytics teams — ensuring accuracy, trust, and accessibility
Lead platform modernization, including the adoption of scalable lakehouse architectures (Databricks, Spark, Delta), CI/CD for data, and observability frameworks
Drive adoption of scalable data practices across Dropbox through reusable tooling, process improvements, and cross-team collaboration
Partner with stakeholders (e.g., Finance, Product, Data Science, and Infrastructure) to understand data needs and deliver solutions that drive real business outcomes.
Mentor and uplift other engineers, helping to cultivate a high-performing, innovation-driven data engineering culture

AWSPythonSQLApache AirflowData AnalysisETLSnowflakeData engineeringData StructuresSparkCI/CDRESTful APIsData visualizationData modelingScriptingData management

Posted 3 months ago

Apply

🔥 Staff Data Engineer

Posted 3 months ago

📍 United States, Canada

🧭 Full-Time

💸 200000.0 - 228000.0 USD per year

🔍 Software Development

🏢 Company: Later👥 1-10 Consumer Electronics iOS Apps Software

🔧 Requirements

10+ years of experience in data engineering, software engineering, or related fields.
Proven experience leading the technical strategy and execution of large-scale data platforms.
Expertise in cloud technologies (Google Cloud Platform, AWS, Azure) with a focus on scalable data solutions (BigQuery, Snowflake, Redshift, etc.).
Strong proficiency in SQL, Python, and distributed data processing frameworks (Apache Spark, Flink, Beam, etc.).
Extensive experience with streaming data architectures using Kafka, Flink, Pub/Sub, Kinesis, or similar technologies.
Expertise in data modeling, schema design, indexing, partitioning, and performance tuning for analytical workloads, including data governance (security, access control, compliance: GDPR, CCPA, SOC 2)
Strong experience designing and optimizing scalable, fault-tolerant data pipelines using workflow orchestration tools like Airflow, Dagster, or Dataflow.
Ability to lead and influence engineering teams, drive cross-functional projects, and align stakeholders towards a common data vision.
Experience mentoring senior and mid-level data engineers to enhance team performance and skill development.

💡 Responsibilities

Lead the design and evolution of a scalable data architecture that meets analytical, machine learning, and operational needs.
Architect and optimize data pipelines for batch and real-time data processing, ensuring efficiency and reliability.
Implement best practices for distributed data processing, ensuring scalability, performance, and cost-effectiveness of data workflows.
Define and enforce data governance policies, implement automated validation checks, and establish monitoring frameworks to maintain data integrity.
Ensure data security and compliance with industry regulations by designing appropriate access controls, encryption mechanisms, and auditing processes.
Drive innovation in data engineering practices by researching and implementing new technologies, tools, and methodologies.
Work closely with data scientists, engineers, analysts, and business stakeholders to understand data requirements and deliver impactful solutions.
Develop reusable frameworks, libraries, and automation tools to improve efficiency, reliability, and maintainability of data infrastructure.
Guide and mentor data engineers, fostering a high-performing engineering culture through best practices, peer reviews, and knowledge sharing.
Establish and monitor SLAs for data pipelines, proactively identifying and mitigating risks to ensure high availability and reliability.

AWSPythonSQLApache AirflowCloud ComputingData AnalysisETLGCPKafkaMachine LearningSnowflakeData engineeringData modelingData management

Posted 3 months ago

Apply

🔥 Staff Data Engineer

Posted 4 months ago

📍 United States

🧭 Full-Time

💸 130000.0 - 170000.0 USD per year

🔍 Data Engineering

🔧 Requirements

8+ years experience in a data engineering role
Strong knowledge of REST-based APIs and cloud technologies (AWS, Azure, GCP)
Experience with Python/SQL for building data pipelines
Bachelor's degree in computer science or related field

💡 Responsibilities

Design and build data pipelines across various source systems
Collaborate with teams to develop data acquisition and integration strategies
Coach and guide others in scalable pipeline building
Deploy to cloud-based platforms and troubleshoot issues

AWSDockerPythonSQLApache AirflowCloud ComputingETLGCPMachine LearningSnowflakeData engineeringREST APIData modeling

Posted 4 months ago

Apply