Senior Data Engineer - Databricks
Company: DATAECONOMY
Role summary
Senior Data Engineer - Databricks is a full-time role at DATAECONOMY in Raleigh, North Carolina, United States (on-site). Posted 2026-09-10. Experience level: 5-10.
- Job title
- Senior Data Engineer - Databricks
- Company
- DATAECONOMY
- Location
- Raleigh, North Carolina, United States
- Work arrangement
- on-site
- Employment type
- full-time
- Category
- Data Science
- Experience level
- 5-10
- Date posted
- 2026-09-10
This is a fantastic opportunity to join DATAECONOMY as a Senior Data Engineer, working with cutting-edge Databricks technology. With a competitive salary and full-time commitment, you'll have a significant impact on data infrastructure and drive innovative solutions.
Job description
DATAECONOMY is one of the fastest-growing Data & Analytics company with global presence. We are well-differentiated and are known for our Thought leadership, out-of-the-box products, cutting-edge solutions, accelerators, innovative use cases, and cost-effective service offerings.
We offer products and solutions in Cloud, Data Engineering, Data Governance, AI/ML, DevOps and Blockchain to large corporates across the globe. Strategic Partners with AWS, Collibra, cloudera, neo4j, DataRobot, Global IDs, tableau, MuleSoft and Talend.
Senior/Lead Data Engineer — Databricks
Raleigh NC
Full-time
Build scalable, production-grade ETL/ELT pipelines using Databricks (PySpark, Spark SQL, Delta Live Tables, Workflows).
Ingest structured, semi-structured, and streaming data into Bronze, Silver, and Gold layers.
Develop optimized transformations, data quality rules, and reusable framework components.
Implement best practices for job orchestration, monitoring, alerting, and automation.
Hands-on experience: Spark, Delta Lake, Workflows, Unity Catalog.
Strong SQL programming and performance tuning skills.
Experience with cloud environments (AWS/Azure/GCP).
Experience with modern data lakehouse concepts and distributed systems.
Strong understanding of Lakeflow Connect, LSDP/Lakehouse, Medallion Architecture, Data Validations, Genie, and Agent Bricks/RAG use cases.
Should be able to explain these concepts using real project examples and architecture decisions.
Requirements
Strong Python (PySpark) and SQL programming
Databricks — Spark, Delta Lake, Workflows, Unity Catalog
ETL/ELT pipeline development — Medallion Architecture (Bronze/Silver/Gold)
Delta Live Tables, Auto-Loader, Structured Streaming
Data modeling — dimensional (star/snowflake), normalization/denormalization
CI/CD, Git, job orchestration
Cloud experience — AWS, Azure, or GCP
7–10+ years in data engineering
Nice-to-Have Skills
Lakeflow Connect, LSDP/Lakehouse, Genie, Agent Bricks/RAG use cases
Data governance, metadata management, Unity Catalog advanced features
Airflow, dbt, or similar orchestration tools
Data security, compliance, and access models
Cost optimization and performance tuning in cloud environments
Corporate/enterprise data warehousing background