Data Engineer

ActioNet is hiring a Data Engineer to help modernize legacy systems into scalable cloud-native architectures. The role builds and maintains data pipelines, ETL workflows, and analytical products while collaborating with software engineering, DevOps, data science, and product teams.

Responsibilities:

• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver tailored data solutions
• Develop efficient data processing and transformation workflows to support analytics and reporting needs
• Design, build, and maintain data pipelines and automated extract, transform, load (ETL) processes using tools like Python, R, and platform‑specific environments such as Jupyter Notebooks
• Integrate disparate structured and unstructured data from APIs, databases, and cloud storage into unified datasets utilizing ETL patterns, frameworks, query techniques
• Implement processes for data cleaning, transformation, and validation to ensure data accuracy, consistency, and compliance with security and privacy policies
• Develop dashboards, visualizations, and analytical products leveraging QuickSight or other mission‑approved tools to support operational decision‑making
• Provide full lifecycle assistance in deploying, optimizing, maintaining complex code with data processing routines running in development, test, and production
• Optimize code through advanced algorithmic concepts to facilitate more efficient

Requirements:

• Candidates must be US Citizens to be eligible
• 5+ years of experience as a Data Engineer, Data Scientist, or Backend Software Engineer
• Bachelor's degree from an accredited college or university with a major in computer science, statistics, mathematics, economics, or related field
• Strong skills in Python and SQL and proficiency with other data engineering languages (e. g., R, SAS, SCALA)
• Proficient in handling large-scale data projects involving data integration, cleaning, ETL, analysis, aggregation, tabulation, and reporting
• Experience developing and implementing data reliability, efficiency, and qualify checks and processes
• Experience leveraging AWS services (e.g., S3, EMR, Glue, Lambda, Athena, Redshift, SageMaker, QuickSight) to build and deploy data solutions in a cloud-native environment
• Experience with structured and unstructured data databases including Oracle, PostGreSQL, MySQL, Athena, Redshift, MongoDB etc
• Familiarity with demographic, economic, and geospatial data sources and structures
• Experience working in an Agile organization using Scrum, Kanban, Jira, Confluence, and SAFe
• Excellent communication and teamwork skills
• Strong skills preparing and presenting design/architectural documents to clients
• Experience with SAS
• Experience with data platforms like Cube, Athena, Redshift, Apache Spark, Databricks, Palantir, Snowflake, Google BigQuery
• Experience with AWS BI and AI/ML services including QuickSight, SPICE, SageMaker etc
• Experience with workflow orchestration tools e.g. Airflow, Temporal
• Familiarity with distributed high-performance computing (HPC) and parallel processing
• Experience with and interest in AI/ML and data modeling
• Experience with microservices architecture and containerization (e.g., Docker, Kubernetes)
• Knowledge of DevOps practices and tools (e.g., Jenkins, GitLab CI/CD)
• Familiarity with agile development methodologies and version control systems (e.g., GitHub, Bitbucket)
• Experience with SAS highly preferred
• Experience with and interest in AI/ML and data modeling highly preferred