Gainwell TechnologiesRemote
Senior Data Engineer
United States of America
Full Time
2 weeks ago
$69,000 - $99,000 USD
H1B Sponsor Likely
Key skills
PythonSQLETLELTData EngineeringData LakeAnalyticsLookerBITableauPower BIDatabricksSparkAirflowAWSLambdaS3GlueVersion ControlCI/CD
About this role
Gainwell Technologies is dedicated to improving the health and well-being of vulnerable communities through innovative technology. The Senior Data Engineer will design, develop, and maintain scalable data pipelines and models, collaborating across teams to ensure data accessibility for analytics and decision-making.
Responsibilities:
- Architect Scalable Data Pipelines: Design, develop, and maintain reliable ETL/ELT workflows using Databricks, Spark, and Python
- Enable Data Access & Analytics: Partner with analytics, product, and engineering teams to ensure timely, accurate, and governed access to data for downstream reporting and analytics
- Optimize Data Workflows: Improve performance, reduce latency, and streamline processes by tuning SQL, optimizing Spark jobs, and enhancing cloud data pipelines
- Leverage Cloud Infrastructure: Utilize AWS services (e.g., S3, Glue, Lambda) to manage and scale data engineering workloads
- Drive Best Practices: Establish and maintain data engineering standards, including code quality, data security, version control, and documentation
- Build & Maintain Data Models: Construct and support dimensional and normalized data models that support cross-functional use cases and reporting needs
- Automation & Monitoring: Set up robust pipeline orchestration (e.g., with Airflow, Databricks Jobs, or AWS Step Functions) and monitoring/alerting systems
- Collaborate Cross-Functionally: Work with data analysts, scientists, and business users to understand requirements and transform raw data into business-ready datasets
Requirements:
- 3+ years of experience as a Data Engineer or in a similar role
- Strong hands-on experience with Databricks (Spark, Delta Lake) and Python-based ETL frameworks
- Solid experience working with AWS cloud services for data processing and storage
- Moderate-to-advanced proficiency in SQL for data wrangling, transformation, and performance tuning
- Experience with data lake architectures, ELT/ETL development, and orchestration tools
- Familiarity with software engineering best practices, including CI/CD, version control, and code reviews
- Experience with Power BI or other BI tools (e.g., Tableau, Looker) to assist in data visualization or self-service reporting enablement