Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("All roles in Dallas, United States"), this listing's salary midpoint is about 10% lower. The offer still falls within the benchmark range (€8,102–€16,834). The listed pay band (€10,000–€12,500) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 3 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: Data Engineer | €2,758/per month | €5,000/per month | €7,000/per month |
| All roles in Dallas, United States | €8,102/per month | €11,477/per month | €16,834/per month |
| From job ad (Senior) | €10,000/per month | €11,250/per month | €12,500/per month |
Job Title: DataBrick Data Engineer Location: Across USA any Location Job Summary The Databricks Data Engineer owns the end-to-end migration strategy, target architecture design, and technical execution of moving legacy ETL workloads to the Databricks Lakehouse. He will establish migration standards, optimize PySpark pipelines, orchestrate complex data workflows, and deploy proprietary automation tools to ensure a seamless, high-performing transition from legacy systems. Key Responsibilities Architectural Strategy & Governance - Design the target Databricks Lakehouse architecture utilizing Delta Lake, Photon, and Unity Catalog. - Establish global code refactoring standards, optimization benchmarks, and PySpark best practices. - Resolve highly complex dependency mappings and architect seamless, zero-downtime dual-run strategies. - Lead the technical deployment and integration of specialized migration accelerators Hands-on Engineering & Optimization - Review automated output from migration tools and manually refactor complex legacy logic into high-performing PySpark notebooks. - Eliminate legacy anti-patterns such as massive row-by-row processing and inefficient lookups. - Optimize PySpark code performance using advanced Spark features including Z-Ordering, partitioning, and caching. - Build robust Databricks Workflows and orchestrate complex DAGs based on comprehensive source lineage. Technical Skills & Competencies - Core Platforms: Databricks, Delta Lake, Unity Catalog, Photon, DataStage. - Languages & Frameworks: PySpark, Python, SQL, Shell Scripting. - Cloud & DevOps: AWS alongside CI/CD deployment pipelines. - Orchestration: Apache Airflow, Databricks Workflows. The pay range for this role is $120k - $150k per annum including any bonuses or variable pay. Tech Mahindra also offers benefits like medical, vision, dental, life, disability insurance and paid time off (including holidays, parental leave, and sick leave, as required by law).
Job Details
Responsibilities
- Design target Databricks Lakehouse architecture using Delta Lake, Photon, and Unity Catalog
- Establish global code refactoring standards and PySpark best practices
- Resolve complex dependency mappings and architect zero-downtime dual-run strategies
- Refactor legacy logic into high-performing PySpark notebooks
- Optimize PySpark code performance using Z-Ordering, partitioning, and caching
- Build Databricks Workflows and orchestrate complex DAGs
Requirements
- Bachelor’s or Higher Degree
- 8.00 to 10.00 Years of experience
Skills & Technologies
Education Level
Bachelor
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