The Role
Lead the design and development of scalable Azure data pipelines and ETL/ELT solutions using Python, PySpark, SQL, Databricks, Data Factory, Synapse, and related Azure services. Provide technical leadership through code reviews, documentation, troubleshooting, mentoring, and engineering best practices. Collaborate with cross-functional teams to translate business requirements into technical solutions and support data warehousing, lakehouse architecture, and governance initiatives.
Summary Generated by Built In
Lead Data EngineerRole Overview
We are looking for a Lead Data Engineer with strong experience in Azure Data Engineering, Python/PySpark, SQL, and Data Warehousing. The role involves designing scalable data pipelines, leading Azure ETL solutions, and providing technical guidance to the team.
Key Responsibilities- Design and develop scalable data pipelines using Python/PySpark.
- Architect and implement Azure ETL/ELT solutions using Databricks, Data Factory, Blob Storage, Synapse, Azure SQL, and Lakebase.
- Work with cross-functional teams to translate business requirements into technical solutions.
- Lead code reviews, ensure engineering best practices, and maintain technical documentation.
- Mentor junior engineers and provide technical leadership.
- Troubleshoot data, pipeline, and performance issues.
- Use Git, Azure DevOps, and Jira for source control and project delivery.
- 8+ years of experience in Data Engineering/Data Warehousing.
- 5+ years of experience with Python/PySpark.
- 8+ years of experience with SQL, including complex queries, stored procedures, and functions.
- Strong experience with Azure Databricks, Data Factory, Blob Storage, Synapse, Azure SQL, Lakebase, and Unity Catalog.
- Knowledge of Azure Functions, Logic Apps, Azure VMs, Git, and Azure DevOps.
- Strong problem-solving, communication, and leadership skills.
- Azure Data Engineer certification is a plus.
- Experience with Lakehouse architecture and data governance.
Role: Lead Data Engineer
Employment: Full-Time, Permanent
Experience: 8+ Years
Education: B.Tech/B.E., BCA, B.Sc., or any relevant postgraduate qualification
Skills Required
- 8+ years of experience in data engineering or data warehousing
- 5+ years of experience with Python and PySpark
- 8+ years of experience with SQL, including complex queries, stored procedures, and functions
- Strong experience with Azure Databricks, Data Factory, Blob Storage, Synapse, Azure SQL, Lakebase, and Unity Catalog
- Knowledge of Azure Functions, Logic Apps, Azure Virtual Machines, Git, and Azure DevOps
- Strong problem-solving, communication, and leadership skills
- Azure Data Engineer certification
- Experience with lakehouse architecture and data governance
- B.Tech, B.E., BCA, B.Sc., or relevant postgraduate qualification
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The Company
What We Do
InXiteOut is a strategic AI and data analytics partner for enterprises. It advises, architects, builds, and deploys production-grade AI solutions, data platforms, analytics systems, custom applications, and automation. The company helps organizations identify high-value use cases, turn complex data into actionable intelligence, and embed AI into daily workflows, enabling faster decisions, smarter operations, measurable business impact, and scalable growth across industries.
