Design, develop, and maintain scalable, secure, and efficient data pipelines and infrastructure that support analytics, reporting, and advanced data science initiatives
Design, build, and optimize ETL/ELT processes for structured and unstructured data
Develop and maintain data pipelines that integrate multiple internal and external data sources
Implement data quality, validation, and monitoring processes to ensure trust in enterprise data assets
Support real-time (streaming) and batch processing pipelines
Collaborate with data architects, analysts, and scientists to deliver scalable data solutions
Implement best practices in data security, governance, and compliance
Contribute to continuous improvement efforts by evaluating and recommending new data engineering tools, techniques, and platforms
Enable data-driven decision-making by ensuring data is reliable, high-quality, and accessible for clients
Requirements
Proficiency in programming languages such as Python, Java, or Scala
Advanced SQL skills for data transformation and performance optimization
Hands-on experience with data pipeline tools (Airflow, dbt, Kafka, or equivalent)
Strong knowledge of big data processing frameworks (Apache Spark, Databricks, Flink, etc.)
Experience with cloud computing platforms (AWS, Azure, Google Cloud)
Familiarity with modern data architectures (data lakes, lakehouses, warehouses)
Exposure to containerization and orchestration tools (Docker, Kubernetes)
Understanding of data modeling, metadata management, and data lineage
Experience implementing CI/CD pipelines for data workflows
Familiarity with modern storage and query engines (Snowflake, Redshift, BigQuery, Delta Lake)
Strong analytical and problem-solving abilities; ability to work with large, complex datasets
Excellent verbal and written communication skills; ability to explain technical concepts to non-technical stakeholders
Collaborative mindset with the ability to work in cross-functional teams
Preferred: Experience with infrastructure-as-code (Terraform, CloudFormation)
Preferred: Knowledge of data governance frameworks and compliance requirements (GDPR, HIPAA, FedRAMP)
Preferred: Familiarity with machine learning data preparation pipelines (feature engineering, MLflow)
Preferred: Background in federal or highly regulated environments is a plus
Benefits
401(k) Plan (35% employer match per dollar up to 10% employee contribution)
Medical Coverage (3 platforms: UnitedHealthcare, Reference Based Pricing includes comprehensive member advocacy; and Kaiser)
HSA with + Employer Contribution
In-vitro Fertility (treatment coverage)
Dental
Vision (2 plans: 12-month and 24-month frames allowance)
FSA Plans (Healthcare, Dependent care and Limited Purpose)
Pre-tax Commuter Plans
Employer-paid Life Insurance
Employer-paid Short + Term Disability
Long Term Disability (2 plans: Employer-paid and Self-paid with non-taxable claim payments)
Paid Parental Leave (4 weeks at 100%)
Employee Assistance Plan
Voluntary Life Insurance
Legal/ID Theft Plans
TeleHealth Options
Wellness via Omada Health (healthy living solution)
Travel Assistance
Business Travel Accident Coverage
Employer-paid Pet Telehealth
Accident Insurance
Critical Illness Insurance
Hospital Indemnity Insurance
Volunteer Time Off
On Demand Pay (Daily Pay)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
