Technical Data Engineer -Databricks

ShyftLabs; Coimbatore District; On-site; INR 1,200,000 - 2,500,000; Full time

Benefits offered by this job

Competitive salary

Insurance package

Learning & development resources

Job summary

ShyftLabs is rapidly growing as a data product company that partners with Fortune 500 firms. We are seeking a Data Engineer to build scalable datapipelines on the Databricks Lakehouse Platform, leveraging Python, PySpark, SQL, AWS, and REST API integrations for data ingestion and export.

The role focuses on designing end-to-end data engineering solutions, implementing Delta Lake with Medallion Architecture, and delivering production-ready pipelines with strong data governance and quality

Qualifications

• Strong expertise in Python, PySpark, and Advanced SQL.
• Hands-on experience with the Databricks Lakehouse Platform.
• Knowledge of Unity Catalog, Delta Lake, Databricks Workflows/Jobs, Clusters, Notebooks, Repos.
• Experience integrating with REST APIs for data ingestion and data export.
• Strong ETL/ELT development, batch processing, incremental loading, and data transformation.

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.

Skills

Python

PySpark

SQL

Databricks

REST APIs

ETL/ELT

Tools

Databricks Lakehouse Platform

Unity Catalog

Delta Lake

Databricks Workflows/Jobs

Clusters

Notebooks

Repos

Job description

Position Overview

We are looking for a Data Engineer with hands-on experience in building scalable datapipelines and data engineering solutions on the Databricks Lakehouse Platform. The idealcandidate should have strong expertise in Python, PySpark, SQL, Databricks, AWS, andREST 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, andREST 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.
• Data Governance experience would be an added advantage.
• Experience with data modeling (Star Schema, Snowflake Schema, Fact & Dimensiontables, 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 queryoptimization.
• Experience with Git and CI/CD best practices

Preferred Qualifications

• 4+ years of experience in Data Engineering with 2+ years of hands-on Databricks experience. Data Governance experience would be an added advantage.
• Experience with Auto Loader, Spark Declarative pipelines, Kafka, Airflow, or dbt is aplus.
• 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.