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191 jobs found.

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🔥 Senior Data Engineer

Posted about 9 hours ago

📍 United States

💸 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

AWS Python SQL Apache Airflow Data Mining ETL Snowflake Algorithms Amazon Web Services Data engineering Data Structures Spark CI/CD RESTful APIs Microservices JSON Scala Data visualization Data modeling Data analytics Data management

Posted about 9 hours ago

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🔥 Solutions Architect

Posted about 9 hours ago

📍 United States, Latin America, India

🔍 Software Development

🔧 Requirements

8+ years as a hands-on Solutions Architect and/or Data Engineer
Programming expertise in Java, Python and/or Scala
Core cloud data platforms including Snowflake, AWS, Azure, Databricks and GCP
SQL and the ability to write, debug, and optimize SQL queries
4-year Bachelor's degree in Computer Science or a related field
Production experience in core data platforms: Snowflake, AWS, Azure, GCP, Hadoop, Databricks

💡 Responsibilities

Design and implement data solutions
Lead and/or mentor other engineers
Develop end-to-end technical solutions into production — and to help ensure performance, security, scalability, and robust data integration
Programming expertise in Java, Python and/or Scala
Client-facing written and verbal communication skills and experience
Create and deliver detailed presentations
Detailed solution documentation (e.g. including POCS and roadmaps, sequence diagrams, class hierarchies, logical system views, etc.)

AWS Leadership Python SQL Cloud Computing ETL GCP Java Snowflake Azure Data engineering REST API Spark Presentation skills Documentation Client relationship management Scala Data visualization Mentorship Data modeling

Posted about 9 hours ago

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🔥 Senior Data Engineer - (Remote - US)

Posted about 11 hours ago

📍 United States

💸 135000.0 - 155000.0 USD per year

🔍 Software Development

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

🔧 Requirements

8+ years of experience as a data engineer, with a strong background in data lake systems and cloud technologies.
4+ years of hands-on experience with AWS technologies, including S3, Redshift, EMR, Kafka, and Spark.
Proficient in Python or Node.js for developing data pipelines and creating ETLs.
Strong experience with data integration and frameworks like Informatica and Python/Scala.
Expertise in creating and managing AWS services (EC2, S3, Lambda, etc.) in a production environment.
Solid understanding of Agile methodologies and software development practices.
Strong analytical and communication skills, with the ability to influence both IT and business teams.

💡 Responsibilities

Design and develop scalable data pipelines that integrate enterprise systems and third-party data sources.
Build and maintain data infrastructure to ensure speed, accuracy, and uptime.
Collaborate with data science teams to build feature engineering pipelines and support machine learning initiatives.
Work with AWS cloud technologies like S3, Redshift, and Spark to create a world-class data mesh environment.
Ensure proper data governance and implement data quality checks and lineage at every stage of the pipeline.
Develop and maintain ETL processes using AWS Glue, Lambda, and other AWS services.
Integrate third-party data sources and APIs into the data ecosystem.

AWS Node.js Python SQL ETL Kafka Data engineering Spark Agile methodologies Scala Data modeling Data management

Posted about 11 hours ago

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🔥 Machine Learning Solutions Architect

Posted about 14 hours ago

📍 United States, Latin America, India

🔍 Software Development

🔧 Requirements

At least 6 years experience as a Machine Learning Engineer, Software Engineer, or Data Engineer
4-year Bachelor's degree in Computer Science or a related field
Experience deploying machine learning models in a production setting
Expertise in Python, Scala, Java, or another modern programming language
The ability to build and operate robust data pipelines using a variety of data sources, programming languages, and toolsets
Strong working knowledge of SQL and the ability to write, debug, and optimize distributed SQL queries
Hands-on experience in one or more big data ecosystem products/languages such as Spark, Snowflake, Databricks, etc.
Familiarity with multiple data sources (e.g. JMS, Kafka, RDBMS, DWH, MySQL, Oracle, SAP)
Systems-level knowledge in network/cloud architecture, operating systems (e.g., Linux), and storage systems (e.g., AWS, Databricks, Cloudera)
Production experience in core data technologies (e.g. Spark, HDFS, Snowflake, Databricks, Redshift, & Amazon EMR)
Development of APIs and web server applications (e.g. Flask, Django, Spring)
Complete software development lifecycle experience, including design, documentation, implementation, testing, and deployment
Excellent communication and presentation skills; previous experience working with internal or external customers

💡 Responsibilities

Design and create environments for data scientists to build models and manipulate data
Work within customer systems to extract data and place it within an analytical environment
Learn and understand customer technology environments and systems
Define the deployment approach and infrastructure for models and be responsible for ensuring that businesses can use the models we develop
Demonstrate the business value of data by working with data scientists to manipulate and transform data into actionable insights
Reveal the true value of data by working with data scientists to manipulate and transform data into appropriate formats in order to deploy actionable machine learning models
Partner with data scientists to ensure solution deployability—at scale, in harmony with existing business systems and pipelines, and such that the solution can be maintained throughout its life cycle
Create operational testing strategies, validate and test the model in QA, and implementation, testing, and deployment
Ensure the quality of the delivered product

AWS Docker Python Software Development SQL Cloud Computing Data Analysis ETL Hadoop Java Keras Kubernetes Machine Learning MLFlow Snowflake Software Architecture Algorithms API testing Data engineering Data science REST API Spark Tensorflow Communication Skills Analytical Skills CI/CD Linux DevOps Presentation skills Excellent communication skills Scala Data modeling Debugging

Posted about 14 hours ago

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🔥 Future Opportunity - Senior Data Engineers Apply Here!

Posted about 15 hours ago

📍 United States, Latin America, India

🔍 Software Development

🔧 Requirements

At least 4+ years experience as a Software Engineer, Data Engineer or Data Analyst
Programming expertise in Java, Python and/or Scala
Core cloud data platforms including Snowflake, AWS, Azure, Databricks and GCP
SQL and the ability to write, debug, and optimize SQL queries
Client-facing written and verbal communication skills and experience
4-year Bachelor's degree in Computer Science or a related field

💡 Responsibilities

Develop end-to-end technical solutions into production — and to help ensure performance, security, scalability, and robust data integration.
Create and deliver detailed presentations
Detailed solution documentation (e.g. including POCS and roadmaps, sequence diagrams, class hierarchies, logical system views, etc.)

AWS Python SQL Cloud Computing Data Analysis ETL GCP Java Kafka Snowflake Airflow Azure Data engineering Spark Communication Skills Scala Data modeling Software Engineering

Posted about 15 hours ago

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🔥 Staff Software Engineer, Data Platform

Posted about 17 hours ago

📍 United States

🧭 Full-Time

💸 240000.0 - 265000.0 USD per year

🔍 Software Development

🏢 Company: TRM Labs👥 101-250💰 $70,000,000 Series B over 2 years agoCryptocurrency Compliance Blockchain Big Data

🔧 Requirements

7+ years of hands-on experience in architecting distributed system architecture, guiding projects from initial ideation through to successful production deployment.
Exceptional programming skills in Python, as well as adeptness in SQL or SparkSQL.
In-depth experience with data stores such as Icerberg, Trino, BigQuery, and StarRocks, and Citus.
Proficiency in data pipeline and workflow orchestration tools like Airflow, DBT, etc.
Expertise in data processing technologies and streaming workflows including Spark, Kafka, and Flink.
Competence in deploying and monitoring infrastructure within public cloud platforms, utilizing tools such as Docker, Terraform, Kubernetes, and Datadog.
Proven ability in loading, querying, and transforming extensive datasets.

💡 Responsibilities

Build highly reliable data services to integrate with dozens of blockchains.
Develop complex ETL pipelines that transform and process petabytes of structured and unstructured data in real-time.
Design and architect intricate data models for optimal storage and retrieval to support sub-second latency for querying blockchain data.
Oversee the deployment and monitoring of large database clusters with an unwavering focus on performance and high availability.
Collaborate across departments, partnering with data scientists, backend engineers, and product managers to design and implement novel data models that enhance TRM’s products.

AWS Docker Python SQL Cloud Computing ETL Kafka Kubernetes Airflow Data engineering Postgres Spark Terraform Data modeling

Posted about 17 hours ago

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🔥 DevOps Engineer (Medellín)

Posted 1 day ago

📍 Medellín, Antioquia, Colombia

🔍 Software Development

🏢 Company: Coactive AI👥 11-50💰 $30,000,000 Series B 10 months agoArtificial Intelligence (AI)Big Data Machine Learning Information Technology

🔧 Requirements

5+ years extensive experience in cloud infrastructure, particularly with AWS, and knowledge of GCP and Azure.
Hands-on expertise in Kubernetes, including deployment, scaling, and management, as well as related tools like Envoy and Keda.
Proficiency with data platforms and tools, including Kafka, Spark, and Databricks.
Strong Python programming skills for automation and infrastructure management.
Solid understanding of networking concepts and experience setting up and managing network infrastructure.
Experience with monitoring and logging tools, such as Datadog, to ensure observability and system reliability.
Proven experience with databases like MongoDB, Postgres, and Redis.
Ability to work independently in a fast-paced startup environment and solve complex problems with minimal guidance.

💡 Responsibilities

Design, build, and maintain highly scalable and reliable infrastructure on cloud platforms like AWS, GCP, and Azure.
Develop and optimize CI/CD pipelines to streamline deployment processes for microservices and data pipelines.
Manage and enhance real-time data workflows using technologies such as Kafka, Spark, and Databricks.
Implement robust monitoring and logging solutions to ensure system health and performance using tools like Datadog.
Establish and enforce cloud security best practices to ensure the integrity and safety of data and applications.
Automate infrastructure using tools like Terraform and orchestrate workloads with Kubernetes and related technologies.
Collaborate with ML and data engineering teams to create a seamless integration between infrastructure and data models.
Ensure efficient network setup and manage databases such as MongoDB, Postgres, and Redis.

AWS Docker PostgreSQL Python Bash Cloud Computing GCP Kafka Kubernetes MongoDB Azure Redis Spark CI/CD RESTful APIs Terraform Microservices Networking Ansible

Posted 1 day ago

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🔥 Sr. Data Engineer

Posted 2 days ago

📍 United States

🔍 Software Development

🏢 Company: ge_externalsite

🔧 Requirements

Exposure to industry standard data modeling tools (e.g., ERWin, ER Studio, etc.).
Exposure to Extract, Transform & Load (ETL) tools like Informatica or Talend
Exposure to industry standard data catalog, automated data discovery and data lineage tools (e.g., Alation, Collibra, TAMR etc., )
Hands-on experience in programming languages like Java, Python or Scala
Hands-on experience in writing SQL scripts for Oracle, MySQL, PostgreSQL or HiveQL
Experience with Big Data / Hadoop / Spark / Hive / NoSQL database engines (i.e. Cassandra or HBase)
Exposure to unstructured datasets and ability to handle XML, JSON file formats

💡 Responsibilities

Work independently as well as with a team to develop and support Ingestion jobs
Evaluate and understand various data sources (databases, APIs, flat files etc. to determine optimal ingestion strategies
Develop a comprehensive data ingestion architecture, including data pipelines, data transformation logic, and data quality checks, considering scalability and performance requirements.
Choose appropriate data ingestion tools and frameworks based on data volume, velocity, and complexity
Design and build data pipelines to extract, transform, and load data from source systems to target destinations, ensuring data integrity and consistency
Implement data quality checks and validation mechanisms throughout the ingestion process to identify and address data issues
Monitor and optimize data ingestion pipelines to ensure efficient data processing and timely delivery
Set up monitoring systems to track data ingestion performance, identify potential bottlenecks, and trigger alerts for issues
Work closely with data engineers, data analysts, and business stakeholders to understand data requirements and align ingestion strategies with business objectives.
Build technical data dictionaries and support business glossaries to analyze the datasets
Perform data profiling and data analysis for source systems, manually maintained data, machine generated data and target data repositories
Build both logical and physical data models for both Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) solutions
Develop and maintain data mapping specifications based on the results of data analysis and functional requirements
Perform a variety of data loads & data transformations using multiple tools and technologies.
Build automated Extract, Transform & Load (ETL) jobs based on data mapping specifications
Maintain metadata structures needed for building reusable Extract, Transform & Load (ETL) components.
Analyze reference datasets and familiarize with Master Data Management (MDM) tools.
Analyze the impact of downstream systems and products
Derive solutions and make recommendations from deep dive data analysis.
Design and build Data Quality (DQ) rules needed

AWS PostgreSQL Python SQL Apache Airflow Apache Hadoop Data Analysis Data Mining Erwin ETL Hadoop HDFS Java Kafka MySQL Oracle Snowflake Cassandra Clickhouse Data engineering Data Structures REST API Nosql Spark JSON Data visualization Data modeling Data analytics Data management

Posted 2 days ago

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🔥 Sr Data Scientist - (Remote - US)

Posted 2 days ago

📍 United States

🔍 Medical device, pharmaceutical, clinical, or biotechnology

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

🔧 Requirements

Proficiency in SQL and programming with R or Python
Experience with Google Cloud Platform (BigQuery, Storage, Compute Engine) is highly valued.
Strong problem-solving skills and the ability to work independently or as part of a team.
Excellent communication skills, able to convey complex statistical concepts to non-technical stakeholders.

💡 Responsibilities

Organize and merge data from diverse sources, ensuring data quality and integrity.
Identify and resolve bottlenecks in data processing and analysis, implementing solutions like automation and optimization.
Collaborate with clinical and technical teams to streamline data collection and entry processes.
Perform statistical analysis, data visualization, and generate reports for clinical studies and other projects.
Prepare summary statistics, tables, figures, and listings for presentations and publications.

Python SQL Apache Airflow Data Mining ETL GCP Algorithms Data engineering Pandas Spark Data visualization Data modeling Data analytics Data management

Posted 2 days ago

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🔥 Data Engineer

Posted 4 days ago

📍 United States

💸 112800.0 - 126900.0 USD per year

🔍 Software Development

🏢 Company: Titan Cloud

🔧 Requirements

4+ years of work experience with ETL, Data Modeling, Data Analysis, and Data Architecture.
Experience operating very large data warehouses or data lakes.
Experience with building data pipelines and applications to stream and process datasets at low latencies.
MySQL, MSSQL Database, Postgres, Python

💡 Responsibilities

Design, implement, and maintain standardized data models that align with business needs and analytical use cases.
Optimize data structures and schemas for efficient querying, scalability, and performance across various storage and compute platforms.
Provide guidance and best practices for data storage, partitioning, indexing, and query optimization.
Developing and maintaining a data pipeline design.
Build robust and scalable ETL/ELT data pipelines to transform raw data into structured datasets optimized for analysis.
Collaborate with data scientists to streamline feature engineering and improve the accessibility of high-value data assets.
Designing, building, and maintaining the data architecture needed to support business decisions and data-driven applications. This includes collecting, storing, processing, and analyzing large amounts of data using AWS, Azure, and local tools and services.
Develop and enforce data governance standards to ensure consistency, accuracy, and reliability of data across the organization.
Ensure data quality, integrity, and completeness in all pipelines by implementing automated validation and monitoring mechanisms.
Implement data cataloging, metadata management, and lineage tracking to enhance data discoverability and usability.
Work with Engineering to manage and optimize data warehouse and data lake architectures, ensuring efficient storage and retrieval of structured and semi-structured data.
Evaluate and integrate emerging cloud-based data technologies to improve performance, scalability, and cost efficiency.
Assist with designing and implementing automated tools for collecting and transferring data from multiple source systems to the AWS and Azure cloud platform.
Work with DevOps Engineers to integrate any new code into existing pipelines
Collaborate with teams in trouble shooting functional and performance issues.
Must be a team player to be able to work in an agile environment

AWS PostgreSQL Python SQL Agile Apache Airflow Cloud Computing Data Analysis ETL Hadoop MySQL Data engineering Data science REST API Spark Communication Skills Analytical Skills CI/CD Problem Solving Terraform Attention to detail Organizational skills Microservices Teamwork Data visualization Data modeling Scripting

Posted 4 days ago

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