Forward Deployed Engineer

ShyftLabs; Coimbatore District; On-site; INR 4,000,000 - 7,000,000; Full time

Benefits offered by this job

Insurance package

Learning & development resources

Job summary

ShyftLabs, a data product company, is seeking a Data Engineer with hands-on experience in building scalable datapipelines on the Databricks Lakehouse Platform. You will work with Python, PySpark, SQL, Databricks, AWS, and REST API integrations to ingest, manage, and export large volumes of data.

The ideal candidate has 9+ years of data engineering experience, including lead roles, and will design and optimize Delta Lake tables, Unity Catalog, and Databricks Jobs while collaborating across teams

Qualifications

• Strong experience with Python, PySpark and SQL in data engineering projects.
• Hands-on with the Databricks Lakehouse Platform and REST API integrations.
• Experience managing large data volumes and building scalable ETL/ELT pipelines.

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 development

Data modeling

Git & CI/CD

Tools

Databricks Unity Catalog

Delta Lake

Medallion Architecture

Databricks Workflows/Jobs

Clusters

Notebooks

Repos

Auto Loader

Kafka

Airflow

dbt

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.


• 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

• 9+ years of experience in Data Engineering, including 3+ years of hands‑on experience with Databricks.


• Prior experience in a Lead Data Engineer / Technical Lead role, with experience guiding engineers and driving technical decisions.


• Strong hands‑on experience with Databricks, Apache Spark, and SQL.


• Experience designing, developing, and optimizing ETL/ELT data pipelines.


• Experience with Auto Loader, Spark Declarative pipelines, Kafka, Airflow, or dbt is a plus.


• Databricks certification is an added advantage. Give me Jd for lead role

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.