Technical Data Engineer (Databricks)

Job details

Work model

Hybrid

Salary

Not listed by source

Location

Coimbatore

Hiring context

How this role compares at ShyftLabs

ShyftLabs has 26 live roles in MeritLog’s catalog across 5 job families, and 11 of them are in data & analytics. 4 of those listings publish a pay range, a disclosure rate of 15%.

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

Job description

Position Overview We are looking for a Data Engineer with hands-on experience in building scalable data pipelines and data engineering solutions on the Databricks Lakehouse Platform. The ideal candidate should have strong expertise in Python, PySpark, SQL, Databricks, AWS, and REST API integrations for data ingestion, managing large volumes of data, and data export ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation. Job Responsibilities: 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. Basic Qualification: 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 (Star Schema, Snowflake Schema, Fact & Dimension tables, SCD concepts). ● Understanding of data warehousing concepts and best practices. ● Experience working with structured and semi-structured data (CSV, JSON, Parquet, Delta). ● Knowledge of partitioning, file optimization, Spark performance tuning, and query optimization. ● Experience with Git and CI/CD best practices Preferred Qualifications: 5+ years of experience in Data Engineering with 2+ years of hands-on Databricks experience. ● Experience with Auto Loader, Spark Declarative pipelines, Kafka, Airflow, or dbt is a plus. ● Databricks certification is an added advantage. We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources.

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