Key skills
PythonScalaSQLRAIMLJupyterETLData EngineeringAnalyticsBISnowflakeBigQueryRedshiftDatabricksSparkApache SparkAirflowAWSKubernetesDockerJenkinsGitLab CILambdaS3GlueAthenaSageMakerCloud StoragePostgreSQLMySQLMongoDBOracleGitHubGitLabBitbucketVersion ControlJiraConfluenceAgileScrumKanbanCI/CDCommunication
About this role
ActioNet is an IT Solutions Provider seeking a Data Engineer to join their interdisciplinary team. The role involves designing and building data solutions that transform legacy systems into cloud-native architectures for data analytics and reporting.
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:
- 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 quality 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
- Requires a Public Trust - must be US Citizen to be eligible
- Experience with SAS highly preferred
- 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 highly preferred
- 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)