Lead Data Engineer

Role & responsibilities

Mandate skills - Pyspark + Azure DataBricks + Azure Data Factory

Experience- 8+ years

We are looking for an experienced and hands-on Data Engineering Lead to guide and mentor a team of data

engineers in delivering scalable and reliable data solutions. This role demands strong technical expertise in Azure

Databricks, Azure Data Factory, and PySpark, along with proven experience in leading data projects, managing

stakeholders, and driving data platform best practices.

As a Data Lead, you will play a critical role in architecting and executing the organizations data strategy while

fostering a high-performance team culture.

Key Responsibilities:

• Lead the design and implementation of robust data pipelines and architectures using Azure Databricks,

ADF, and PySpark.

• Provide technical leadership and mentoring to a team of data engineers.
• Drive the adoption of best practices in data engineering, coding standards, and data quality assurance.
• Collaborate with cross-functional teams including data science, product, business, and analytics to define

and deliver data-driven solutions.

• Own end-to-end delivery of data initiatives, ensuring projects are delivered on time and within scope.
• Architect scalable solutions using Azure cloud-native services, ensuring performance, security, and cost

optimization.

• Establish and monitor SLAs for data pipelines, orchestrate job schedules, and ensure high availability.
• Act as a key stakeholder in data governance, data cataloging, and metadata management efforts.
• Drive continuous improvement in development processes, automation, and CI/CD pipelines.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related discipline.
• 5+ years of experience in data engineering, with 2+ years in a leadership or team lead capacity.
• Proven expertise in:
• Azure Databricks (including Delta Lake, Spark optimizations)
• Azure Data Factory
• PySpark
• Hands-on experience with Azure Data Lake, SQL, and distributed data processing.
• Solid understanding of data architecture patterns, data modeling, and performance tuning.
• Strong experience in stakeholder management and cross-functional collaboration.
• Experience with CI/CD tools (Azure DevOps, GitHub Actions, etc.) and DevOps practices.
• Knowledge of cloud cost optimization, security, and compliance in Azure.

Preferred Qualifications:

• Experience with Azure Synapse Analytics, Azure Functions, Event Hubs, or Stream Analytics.
• Familiarity with Agile/Scrum methodologies.
• Exposure to data governance frameworks and tools like Purview.
• Understanding of business KPIs and ability to translate business needs into technical solutions.
• Excellent communication, leadership, and people management skills.