Lead Data Engineer - Databricks

ShyftLabs; United States; Remote; USD 140,000 - 200,000; Full time

Benefits offered by this job

Insurance package

Learning & development resources

Job summary

ShyftLabs is seeking a Data Engineer to design and scale ETL/ELT pipelines on the Databricks Lakehouse. You will ingest and export data via REST APIs, build with PySpark and SQL, and implement robust data models using Delta Lake and Medallion Architecture.

You will optimize Spark performance, schedule Databricks Jobs, and collaborate across teams to deliver reliable data solutions for Fortune 500 clients. This is a senior, hands-on role with emphasis on scalability and quality.

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.
• 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

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, PySpark, and SQL.
• Integrate data from multiple sources, including databases, S3, files, and REST APIs.
• Build data pipelines with Databricks Unity Catalog.
• Implement business logic, data transformations, and dimensional 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 API integration

ETL/ELT

Data modeling

Data warehousing

Git & CI/CD

Spark performance tuning

Tools

Databricks

Apache Spark

SQL

Git

Airflow

Kafka

dbt

Unity Catalog

Delta Lake

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.

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.