Technical Data Engineer -Databricks

Simfluent; Coimbatore; On-site; INR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Competitive salary

Insurance package

Learning & development resources

Job summary

ShyftLabs is seeking a Data Engineer to build scalable data pipelines on the Databricks Lakehouse Platform. You will leverage Python, PySpark, and SQL to ingest, transform, and export large data sets across AWS services and REST APIs.

Responsibilities include designing ETL/ELT pipelines, orchestrating Databricks Jobs, and managing Delta Lake tables using a Medallion Architecture. Collaboration with cross-functional teams will be essential to deliver production-ready data solutions.

Qualifications

• 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.

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.
• 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.

Skills

Python

PySpark

Advanced SQL

ETL/ELT development

Data modeling

Tools

Databricks Lakehouse Platform

Databricks Workflows/Jobs

Unity Catalog

Delta Lake

Medallion Architecture

AWS

REST APIs

S3

Git

CI/CD

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.