Data Engineer
About The Position
Design, develop, and maintain robust data pipelines and ETL/ELT processes to ingest, transform, and load data from diverse structured and unstructured sources. Build and optimize data models and data architectures to support analytics, reporting, and operational use cases. Implement and maintain CI/CD pipelines for data engineering workflows, including data pipelines and scheduled jobs, using version control and automation tools. Develop and deploy cloud-based data solutions, leveraging services such as object storage, serverless compute, and messaging/queueing services. Collaborate with database administrators, analysts, and application teams to integrate data sources, design schemas, and support downstream data consumers. Ensure data quality, integrity, and reliability through validation, monitoring, logging, and alerting. Support data migration, integration, and modernization initiatives, including legacy system upgrades and cloud adoption efforts. Troubleshoot and resolve issues in development and production environments to maintain stable and reliable data pipelines. Document data flows, pipelines, and technical solutions to support knowledge sharing and compliance requirements. Stay current with emerging tools, technologies, and best practices in data engineering and cloud platforms.
Requirements
- US Citizenship or a Green Card is required
- A Bachelor’s degree is required
- A minimum of 4 years of experience in data engineering, software development, or a closely related role is required.
- Proficiency in one or more programming languages commonly used in data engineering (e.g., Python, SQL, R, PySpark, or Java).
- Hands-on experience designing and building data pipelines and ETL/ELT processes leveraging commonly used ETL/ELT tools (e.g., SSIS, Databricks, Azure Data Factory)
- Strong knowledge of relational database design, data warehouses, and/or data lakes using star/snowflake schemas
- Experience working with relational and/or NoSQL databases (e.g., Oracle, Postgres, SQL Server, MongoDB).
- Experience working in a cloud environment (AWS or Azure) supporting data solutions.
- Familiarity with version control and CI/CD practices for data workflows (e.g., Git, Jenkins).
- Exposure to containerization technologies (e.g., Docker; Kubernetes is a plus).
- Experience using monitoring and logging tools to support data pipeline reliability (e.g., CloudWatch, Splunk, Kibana, Elasticsearch).
- Ability to work effectively in an Agile development environment.
- Strong analytical and troubleshooting skills, and the ability to communicate technical concepts clearly to clients, engineers, and business stakeholders
- Ability to work independently in a fast-paced, client-facing environment.
Nice To Haves
- AWS, Azure, Databricks, or other data engineering–related certifications (Datalake of Exasol).
- Experience with data visualization or analytics tools (e.g., Kibana, Tableau, Power BI).
- Familiarity with security, compliance, and data governance best practices in healthcare.
- Exposure to microservices-based architectures or AI/ML-enabled data pipelines.
- Prior consulting experience.
Responsibilities
- Design, develop, and maintain robust data pipelines and ETL/ELT processes to ingest, transform, and load data from diverse structured and unstructured sources.
- Build and optimize data models and data architectures to support analytics, reporting, and operational use cases.
- Implement and maintain CI/CD pipelines for data engineering workflows, including data pipelines and scheduled jobs, using version control and automation tools.
- Develop and deploy cloud-based data solutions, leveraging services such as object storage, serverless compute, and messaging/queueing services.
- Collaborate with database administrators, analysts, and application teams to integrate data sources, design schemas, and support downstream data consumers.
- Ensure data quality, integrity, and reliability through validation, monitoring, logging, and alerting.
- Support data migration, integration, and modernization initiatives, including legacy system upgrades and cloud adoption efforts.
- Troubleshoot and resolve issues in development and production environments to maintain stable and reliable data pipelines.
- Document data flows, pipelines, and technical solutions to support knowledge sharing and compliance requirements.
- Stay current with emerging tools, technologies, and best practices in data engineering and cloud platforms.
Benefits
- Medical, Rx, Dental & Vision Insurance
- Personal and Family Sick Time & Company Paid Holidays
- Position may be eligible for a discretionary variable incentive bonus
- Parental Leave and Adoption Assistance
- 401(k) Retirement Plan
- Basic Life & Supplemental Life
- Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
- Short-Term & Long-Term Disability
- Student Loan PayDown
- Tuition Reimbursement, Personal Development & Learning Opportunities
- Skills Development & Certifications
- Employee Referral Program
- Corporate Sponsored Events & Community Outreach
- Emergency Back-Up Childcare Program
- Mobility Stipend
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees
