Data Engineer - Senior Consultant
About The Position
Develop and maintain scalable data ingestion, transformation, and curation pipelines using Databricks (Delta Lake, Delta Live Tables, Auto Loader) and AWS services, supporting consistent delivery of analytics-ready datasets across the Data Platform. Implement standardized batch and near real-time data pipelines that integrate legacy systems and cloud-native data sources, contributing to enterprise-wide data access, reuse, and platform consistency. Support full data pipeline lifecycle activities, including intake, requirements analysis, source profiling, and technical implementation, aligning development work with defined intake processes, SLAs, and governance. Build production-ready data pipelines that meet defined technical and documentation standards, including participation in validation, testing, and release processes to enable reliable and compliant production deployments. Apply data quality checks, validation rules, and observability practices to improve pipeline reliability, support monitoring, and contribute to platform stability and operational performance targets. Integrate pipelines with AWS services (e.g., S3, streaming frameworks, APIs) and enterprise data tools to support secure, scalable data movement and interoperability across the ecosystem. Contribute to governed data engineering practices by implementing metadata capture, lineage tracking, and supporting access control patterns aligned to enterprise data governance standards. Support analytics and reporting use cases by preparing curated datasets and enabling consumption through SQL-based access, dashboards, and enterprise BI tooling.
Requirements
- Bachelor’s degree is required
- Minimum FOUR (4) years of experience in data engineering, with hands-on development of data pipelines in cloud or distributed data environments.
- Strong proficiency in Python, PySpark, and SQL for building and maintaining scalable ETL/ELT pipelines.
- Experience working with Databricks and Delta Lake to support ingestion, transformation, and curated data layer development.
- Working knowledge of AWS data services (e.g., S3, IAM, VPC) and integration patterns supporting secure and scalable data architectures.
- Experience implementing data quality checks, monitoring, and basic performance optimization techniques for pipeline efficiency and reliability.
- Familiarity with data governance concepts, including metadata, lineage, and access control frameworks in regulated environments.
- Experience working within Agile delivery environments and contributing to CI/CD-enabled development workflows.
Nice To Haves
- Experience supporting enterprise data platforms or federal data modernization initiatives, particularly in highly regulated environments.
- Exposure to streaming technologies such as Kafka, Kinesis, or EventBridge for near real-time data processing.
- Familiarity with Databricks Unity Catalog and governance capabilities (RBAC, data masking, auditing).
- Experience using metadata/catalog tools such as Informatica EDC or similar platforms.
- Understanding of DevSecOps practices, including automated testing, deployment, and environment promotion across dev/test/prod.
- Exposure to performance optimization techniques (e.g., partitioning, Z-ordering, clustering) for large-scale data processing workloads.
Responsibilities
- Develop and maintain scalable data ingestion, transformation, and curation pipelines using Databricks (Delta Lake, Delta Live Tables, Auto Loader) and AWS services.
- Implement standardized batch and near real-time data pipelines that integrate legacy systems and cloud-native data sources.
- Support full data pipeline lifecycle activities, including intake, requirements analysis, source profiling, and technical implementation.
- Build production-ready data pipelines that meet defined technical and documentation standards.
- Apply data quality checks, validation rules, and observability practices to improve pipeline reliability.
- Integrate pipelines with AWS services (e.g., S3, streaming frameworks, APIs) and enterprise data tools.
- Contribute to governed data engineering practices by implementing metadata capture, lineage tracking, and supporting access control patterns.
- Support analytics and reporting use cases by preparing curated datasets and enabling consumption through SQL-based access, dashboards, and enterprise BI tooling.
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
Senior
