Senior Data Engineer

Posted 3 months agoViewed

View full description

💎 Seniority level: Senior, 5+ years

📍 Location: United States

💸 Salary: 100000.0 - 120000.0 USD per year

🔍 Industry: Healthcare

🏢 Company: Found👥 51-100💰 $45,999,997 Series C 10 months agoFinancial Services Banking FinTech

🗣️ Languages: English

⏳ Experience: 5+ years

🪄 Skills: PythonSQLApache AirflowETLSnowflakePandasSpark

Requirements:

5+ years of experience in data engineering or related areas. You are an end-to-end data engineer whose experience goes beyond creating ETL pipelines.
Expertise in SQL and data manipulation languages.
Proficiency in data pipeline tools (Airflow, AWS Glue, Spark/PySpark, Pandas).
Strong programming skills in Python.
Experience with data storage technologies like warehouses (Snowflake, Redshift) and data lakes (Databricks, Glue Catalog/S3).

Responsibilities:

Design, implement, and manage robust and scalable data pipelines to ingest, process, and transform data from various sources.
Develop and maintain data models to support business intelligence, reporting, and analytics needs.
Design and implement data warehousing solutions to store and organize large volumes of data efficiently.
Develop and optimize ETL (Extract, Transform, Load) processes to ensure data accuracy and integrity.
Implement data quality checks and monitoring processes to maintain data integrity and reliability.
Continuously monitor and optimize data pipelines and queries for performance and scalability.
Work closely with data analysts and other stakeholders to understand their data needs and provide solutions.
Create and maintain clear and comprehensive documentation of data architecture, processes, and data dictionaries.

Apply

Related Jobs

Apply

🔥 Senior Data Engineer

Posted 5 days ago

📍 Worldwide

🔍 Hospitality

🏢 Company: Lighthouse

🔧 Requirements

4+ years of professional experience using Python, Java, or Scala for data processing (Python preferred)
You stay up-to-date with industry trends, emerging technologies, and best practices in data engineering.
Improve, manage, and teach standards for code maintainability and performance in code submitted and reviewed
Ship large features independently, generate architecture recommendations and have the ability to implement them
Great communication: Regularly achieve consensus amongst teams
Familiarity with GCP, Kubernetes (GKE preferred), CI/CD tools (Gitlab CI preferred), familiarity with the concept of Lambda Architecture.
Experience with Apache Beam or Apache Spark for distributed data processing or event sourcing technologies like Apache Kafka.
Familiarity with monitoring tools like Grafana & Prometheus.

💡 Responsibilities

Design and develop scalable, reliable data pipelines using the Google Cloud stack.
Optimise data pipelines for performance and scalability.
Implement and maintain data governance frameworks, ensuring data accuracy, consistency, and compliance.
Monitor and troubleshoot data pipeline issues, implementing proactive measures for reliability and performance.
Collaborate with the DevOps team to automate deployments and improve developer experience on the data front.
Work with data science and analytics teams to enable them to bring their research to production grade data solutions, using technologies like airflow, dbt or MLflow (but not limited to)
As a part of a platform team, you will communicate effectively with teams across the entire engineering organisation, to provide them with reliable foundational data models and data tools.
Mentor and provide technical guidance to other engineers working with data.

PythonSQLApache AirflowETLGCPKubernetesApache KafkaData engineeringCI/CDMentoringTerraformScalaData modeling

Posted 5 days ago

Apply

🔥 Senior Data Engineer

Posted 6 days ago

📍 United States

🧭 Full-Time

💸 183600.0 - 216000.0 USD per year

🔍 Software Development

🔧 Requirements

6+ years of experience in a data engineering role building products, ideally in a fast-paced environment
Good foundations in Python and SQL.
Experience with Spark, PySpark, DBT, Snowflake and Airflow
Knowledge of visualization tools, such as Metabase, Jupyter Notebooks (Python)

💡 Responsibilities

Collaborate on the design and improvements of the data infrastructure
Partner with product and engineering to advocate best practices and build supporting systems and infrastructure for the various data needs
Create data pipelines that stitch together various data sources in order to produce valuable business insights
Create real-time data pipelines in collaboration with the Data Science team

PythonSQLSnowflakeAirflowData engineeringSparkData visualizationData modeling

Posted 6 days ago

Apply

🔥 Senior Data Engineer

Posted 6 days ago

📍 United States

🧭 Full-Time

🔍 Healthcare

🏢 Company: Rad AI👥 101-250💰 $60,000,000 Series C 2 months agoArtificial Intelligence (AI)Enterprise Software Health Care

🔧 Requirements

4+ years relevant experience in data engineering.
Expertise in designing and developing distributed data pipelines using big data technologies on large scale data sets.
Deep and hands-on experience designing, planning, productionizing, maintaining and documenting reliable and scalable data infrastructure and data products in complex environments.
Solid experience with big data processing and analytics on AWS, using services such as Amazon EMR and AWS Batch.
Experience in large scale data processing technologies such as Spark.
Expertise in orchestrating workflows using tools like Metaflow.
Experience with various database technologies including SQL, NoSQL databases (e.g., AWS DynamoDB, ElasticSearch, Postgresql).
Hands-on experience with containerization technologies, such as Docker and Kubernetes.

💡 Responsibilities

Design and implement the data architecture, ensuring scalability, flexibility, and efficiency using pipeline authoring tools like Metaflow and large-scale data processing technologies like Spark.
Define and extend our internal standards for style, maintenance, and best practices for a high-scale data platform.
Collaborate with researchers and other stakeholders to understand their data needs including model training and production monitoring systems and develop solutions that meet those requirements.
Take ownership of key data engineering projects and work independently to design, develop, and maintain high-quality data solutions.
Ensure data quality, integrity, and security by implementing robust data validation, monitoring, and access controls.
Evaluate and recommend data technologies and tools to improve the efficiency and effectiveness of the data engineering process.
Continuously monitor, maintain, and improve the performance and stability of the data infrastructure.

AWSDockerSQLElasticSearchETLKubernetesData engineeringNosqlSparkData modeling

Posted 6 days ago

Apply

🔥 Senior Data Engineer - Data Services

Posted 6 days ago

📍 Worldwide

🧭 Full-Time

🔧 Requirements

NOT STATED

💡 Responsibilities

Own the design and implementation of cross-domain data models that support key business metrics and use cases.
Partner with analysts and data engineers to translate business logic into performant, well-documented dbt models.
Champion best practices in testing, documentation, CI/CD, and version control, and guide others in applying them.
Act as a technical mentor to other analytics engineers, supporting their development and reviewing their code.
Collaborate with central data platform and embedded teams to improve data quality, metric consistency, and lineage tracking.
Drive alignment on model architecture across domains—ensuring models are reusable, auditable, and trusted.
Identify and lead initiatives to reduce technical debt and modernise legacy reporting pipelines.
Contribute to the long-term vision of analytics engineering at Pleo and help shape our roadmap for scalability and impact.

SQLData AnalysisETLData engineeringCI/CDMentoringDocumentationData visualizationData modelingData analyticsData management

Posted 6 days ago

Apply

🔥 Senior Data Engineer

Posted 6 days ago

📍 United States

🧭 Full-Time

💸 183600.0 - 216000.0 USD per year

🔍 Mental Healthcare

🏢 Company: Headway👥 201-500💰 $125,000,000 Series C over 1 year agoMental Health Care

🔧 Requirements

6+ years of experience in a data engineering role building products, ideally in a fast-paced environment
Good foundations in Python and SQL.
Experience with Spark, PySpark, DBT, Snowflake and Airflow
Knowledge of visualization tools, such as Metabase, Jupyter Notebooks (Python)
A knack for simplifying data, expressing information in charts and tables

💡 Responsibilities

Collaborate on the design and improvements of the data infrastructure
Partner with product and engineering to advocate best practices and build supporting systems and infrastructure for the various data needs
Create data pipelines that stitch together various data sources in order to produce valuable business insights
Create real-time data pipelines in collaboration with the Data Science team

PythonSQLETLSnowflakeAirflowData engineeringRDBMSSparkRESTful APIsData visualizationData modeling

Posted 6 days ago

Apply

🔥 Senior Data Engineer (AS)

Posted 13 days ago

📍 United States, Canada

🧭 Full-Time

🔍 Software Development

🔧 Requirements

Strong hands-on experience with Python and core Python Data Processing tools such as pandas, numpy, scipy, scikit
Experience with cloud tools and environments like Docker, Kubernetes, GCP, and/or Azure
Experience with Spark/PySpark
Experience with Data Lineage and Data Cataloging
Relational and non-relational database experience
Experience with Data Warehouses and Lakes, such as Bigquery, Databricks, or Snowflake
Experience in designing and building data pipelines that scale
Strong communication skills, with the ability to convey technical solutions to both technical and non-technical stakeholders
Experience working effectively in a fast-paced, agile environment as part of a collaborative team
Ability to work independently and as part of a team
Willingness and enthusiasm to learn new technologies and tackle challenging problems
Experience in Infrastructure as Code tools like Terraform
Advanced SQL expertise, including experience with complex queries, query optimization, and working with various database systems

💡 Responsibilities

Work with business stakeholders to understand their goals, challenges, and decisions
Assist with building solutions that standardize their data approach to common problems across the company
Incorporate observability and testing best practices into projects
Assist in the development of processes to ensure their data is trusted and well-documented
Effectively work with data analysts on refining the data model used for reporting and analytical purposes
Improve the availability and consistency of data points crucial for analysis
Standing up a reporting system in BigQuery from scratch, including data replication, infrastructure setup, dbt model creation, and Integration with reporting endpoints
Revamping orchestration and execution to reduce critical data delivery times
Database archiving to move data from a live database to cold storage

AWSSQLCloud ComputingData AnalysisETLData engineeringData visualizationData modeling

Posted 13 days ago

Apply

🔥 Senior Data Engineer

Posted 23 days ago

📍 United States

🧭 Full-Time

💸 144000.0 - 180000.0 USD per year

🔍 Software Development

🏢 Company: Hungryroot👥 101-250💰 $40,000,000 Series C almost 4 years agoArtificial Intelligence (AI)Food and Beverage E-Commerce Retail Consumer Goods Software

🔧 Requirements

5+ years of experience in ETL development and data modeling
5+ years of experience in both Scala and Python
5+ years of experience in Spark
Excellent problem-solving skills and the ability to translate business problems into practical solutions
2+ years of experience working with the Databricks Platform

💡 Responsibilities

Develop pipelines in Spark (Python + Scala) in the Databricks Platform
Build cross-functional working relationships with business partners in Food Analytics, Operations, Marketing, and Web/App Development teams to power pipeline development for the business
Ensure system reliability and performance
Deploy and maintain data pipelines in production
Set an example of code quality, data quality, and best practices
Work with Analysts and Data Engineers to enable high quality self-service analytics for all of Hungryroot
Investigate datasets to answer business questions, ensuring data quality and business assumptions are understood before deploying a pipeline

AWSPythonSQLApache AirflowData MiningETLSnowflakeAlgorithmsAmazon Web ServicesData engineeringData StructuresSparkCI/CDRESTful APIsMicroservicesJSONScalaData visualizationData modelingData analyticsData management

Posted 23 days ago

Apply

🔥 Senior Data Engineer

Posted 27 days ago

📍 United States

🧭 Full-Time

💸 170000.0 - 190000.0 USD per year

🔍 Software Development

🏢 Company: Productiv👥 101-250💰 $45,000,000 Series C about 4 years agoDeveloper Platform Communities Service Industry SaaS Data Integration Analytics Enterprise Software Software Application Performance Management

🔧 Requirements

Strong experience designing and implementing ETL/ELT data pipelines using modern data stack technologies (e.g., Redshift, Athena, Presto, DynamoDB).
Expertise in data modeling and designing scalable storage solutions for analytics and reporting.
Strong proficiency in SQL, NoSQL, and Javascript
Experience with monitoring, logging, and alerting for data systems to ensure proactive issue resolution.
Experience with data migration to-and-from S3, DynamoDB, Redshift, and Athena.

💡 Responsibilities

Design, build, and maintain scalable, efficient, and reliable data pipelines
Ensure data integrity and quality
Implement monitoring, alerting, and logging systems
Design and optimize data models and storage solutions
Collaborate with cross-functional teams
Continuously improve data engineering processes and standards
Troubleshoot and resolve complex data issues
Mentor and provide technical leadership

AWSSQLApache AirflowDynamoDBETLJavascriptCross-functional Team LeadershipAlgorithmsData engineeringData StructuresREST APINosqlCommunication SkillsCI/CDProblem SolvingMentoringData visualizationData modelingSoftware EngineeringData management

Posted 27 days ago

Apply

🔥 Senior Data Engineer (Remote)

Posted 28 days ago

📍 United States

🧭 Full-Time

💸 170000.0 - 210000.0 USD per year

🔍 Health and Fitness

🔧 Requirements

Minimum of 6 years of experience working in data engineering
Expertise both in using SQL and Python for data cleansing, transformation, modeling, pipelining, etc.
Proficient in working with other stakeholders and converting requirements into detailed technical specifications; owning and leading projects from inception to completion
Proficiency in working with high volume datasets in SQL-based warehouses such as BigQuery
Proficiency with parallelized python-based data processing frameworks such as Google Dataflow (Apache Beam), Apache Spark, etc.
Experience using ELT tools like Dataform or dbt
Professional experience maintaining data systems in GCP and AWS
Deep understanding of data modeling, access, storage, caching, replication, and optimization techniques
Experienced with orchestrating data pipelines and Kubernetes-based jobs with Apache Airflow
Understanding of the software development lifecycle and CI/CD
Monitoring and metrics-gathering (e.g. Datadog, NewRelic, Cloudwatch, etc)
Willingness to participate in a weekly on-call support rotation - currently the rotation is monthly
Proficiency with git and working collaboratively in a shared codebase
Excellent documentation skills
Self motivation and a deep sense of pride in your work
Passion for the outdoors
Comfort with ambiguity, and an instinct for moving quickly
Humility, empathy and open-mindedness - no egos

💡 Responsibilities

Work cross-functionally to ensure data scientists have access to clean, reliable, and secure data, the backbone for new algorithmic product features
Build, deploy, and orchestrate large-scale batch and stream data pipelines to transform and move data to/from our data warehouse and other systems
Deliver scalable, testable, maintainable, and high-quality code
Investigate, test-for, monitor, and alert on inconsistencies in our data, data systems, or processing costs
Create tools to improve data and model discoverability and documentation
Ensure data collection and storage adheres to GDPR and other privacy and legal compliance requirements
Uphold best data-quality standards and practices, promoting such knowledge throughout the organization
Deploy and build systems that enable machine learning and artificial intelligence product solutions
Mentoring others on best industry practices

AWSPostgreSQLPythonSQLApache AirflowCloud ComputingData AnalysisETLApache KafkaData engineeringCI/CDRESTful APIsMicroservicesData visualizationData modelingData analyticsData management

Posted 28 days ago

Apply

🔥 Senior Data Engineer

Posted 29 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, and WI

🧭 Full-Time

🔍 Home Insurance

🏢 Company: Kin Insurance

🔧 Requirements

Experience in data engineering with a focus on warehousing.
Experience with data pipeline tools and platforms such as dbt, Databricks, FiveTran, Kafka, and AWS.
Experience with various data ingestion methods including API ingestion, CDC replication, and JSON ingestion.
Experienced programmer using languages such as SQL, Python, and/or Java.
Previous experience with databases such as AWS Redshift, MySQL, Postgres, SQL Server, etc.
Excellent communication and collaboration skills to engage with stakeholders across different levels of the organization.

💡 Responsibilities

Working on a cross-functional project team with members from AppEng, DataEng, BI, and business stakeholders tasked with designing a solution to produce effective reporting, implementing data validation standards, and QA procedures to ensure effective data lifecycle and management practices.
Establishing trust and relationships with stakeholders while defining technical requirements, ensuring alignment with business goals.
Assess the effectiveness and accuracy of data sources and data gathering techniques.
Maintaining a centralized metadata catalog to document data assets, schemas and lineage.
Design pipelines and data models with a focus on scalability and maintenance.
Analyze database configurations to optimize the performance of end user models and dashboards.
Conduct RCAs and build out future-proof debugging strategies.

AWSPostgreSQLPythonSQLData AnalysisKafkaMySQLAPI testingData engineeringJSONData visualizationData modeling

Posted 29 days ago

Apply