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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates strong expertise in designing and developing scalable ETL/ELT pipelines using Databricks, PySpark, and SQL, while ensuring data quality and optimizing performance. Proficient in data integration from various sources and implementing business logic and data transformations.
Highest-signal resume keywords
PythonPySparkAdvanced SQLDatabricks Lakehouse PlatformETL/ELT Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ModelingData TransformationBatch ProcessingIncremental LoadingDelta LakeSpark Performance TuningQuery OptimizationData WarehousingREST API IntegrationMedallion Architecture
Soft Skills
CollaborationProblem-Solving
Tools & Technologies
DatabricksUnity CatalogDatabricks WorkflowsGitCI/CD
Certifications & Qualifications
Databricks Certification
Industry Keywords
ETLELTData EngineeringStructured DataSemi-Structured DataCSVJSONParquetDeltaAirflow
Tech Stack
Tools & technologiesAirflowETLKafkaPySparkPythonSparkSQLUnity
About the role
Key responsibilities & impact- Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, PySpark, and SQL
- Integrate data from multiple sources, including databases, Amazon S3, files, and REST APIs
- Build data pipelines with Databricks Unity Catalog
- Implement business logic, data transformations, and dimensional data models
- Create, schedule, monitor, and optimize Databricks Jobs and Workflows
- Design and manage Delta Lake tables using Medallion Architecture (Bronze, Silver, Gold)
- Ensure data quality through validations, error handling, logging, and monitoring
- Optimize Spark workloads for performance, scalability, and reliability
- Collaborate with cross-functional teams to deliver production-ready data solutions
Requirements
What you’ll need- Strong expertise in Python, PySpark, and Advanced SQL
- Hands-on experience with the Databricks Lakehouse Platform
- Good understanding of Unity Catalog, Delta Lake, Databricks Workflows/Jobs, Clusters, Notebooks, Repos, and Medallion Architecture
- Experience integrating with REST APIs for data ingestion and data export
- Strong knowledge of ETL/ELT development, batch processing, incremental loading, and data transformation
- Experience with data modeling, including Star Schema, Snowflake Schema, Fact & Dimension tables, and SCD concepts
- Understanding of data warehousing concepts and best practices
- Experience working with structured and semi-structured data, including CSV, JSON, Parquet, and Delta
- Knowledge of partitioning, file optimization, Spark performance tuning, and query optimization
- Experience with Git and CI/CD best practices
- 4+ years of experience in Data Engineering with 2+ years of hands-on Databricks experience (preferred qualifications)
- Experience with Auto Loader, Spark Declarative pipelines, Kafka, Airflow, or dbt is a plus
- Databricks certification is an added advantage
Benefits
Comp & perks- Competitive salary
- Strong insurance package
- Extensive learning and development resources