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Lead Data Engineer
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Job Info
- Job Identification16137
- Posting Date07/08/2026, 08:48 AM
- Job RoleData Engineering-Cloud Data Engineering
- Experience (In Years)6-9
Job Description
We are looking for an accomplished Lead Data Engineer to drive the architectural design, development, and optimization of our enterprise-scale data ecosystem. In this senior role, you will spearhead the build-out of high‑performance data pipelines, enforce rigorous data quality and validation frameworks, and ensure end‑to‑end reliability, scalability, and integrity of data flows across the organization. You will play a pivotal role in shaping our data engineering strategy, enabling advanced analytics and mission‑critical, data‑driven decision-making within our insurance-focused business domains.
Responsibilities
- Lead the design and implementation of scalable data architectures on Azure, leveraging Databricks, Delta Lake, and related Azure data services.
- Build and optimize high‑volume ETL/ELT pipelines using PySpark, SQL, Databricks Workflows, and Delta Live Tables.
- Define and enforce best practices for data engineering across notebooks, jobs, CI/CD, Unity Catalog, security, and workspace governance.
- Integrate and orchestrate data pipelines using Azure Data Factory, Azure Synapse pipelines, or Azure Databricks Workflows.
- Drive performance tuning for Spark jobs, cluster configurations, and data storage layers to balance speed and cost efficiency.
- Implement robust data quality and validation frameworks using tools like Great Expectations, DLT expectations, or custom PySpark checks.
- Ensure compliance, governance, and lineage tracking through Unity Catalog, Purview integration, and RBAC/ABAC policies.
- Architect end‑to‑end data solutions supporting analytics, ML, actuarial models, and business-critical reporting workloads.
- Evaluate new Databricks features, MLflow enhancements, Photon execution, serverless compute, and recommend adoption strategies.
- Familiar with working on Agile methodologies - scrum, sprint planning, backlog refinement etc.
Qualifications
- 8-12 years experience on Data Engineering role working with Databricks & Azure Cloud technologies.
- Bachelor’s degree in computer science, Information Technology, or related field.
- Strong proficiency in PySpark, Python, SQL.
- Strong experience in data modeling, ETL/ELT pipeline development, and automation
- Hands-on experience with performance tuning of data pipelines and workflows
- Proficient in working on Azure cloud components Azure Data Factory, Azure DataBricks, Azure Data Lake etc.
- Experience with data modeling, ETL processes, Delta Lake and data warehousing.
- Experience on Delta Live Tables, Autoloader & Unity Catalog.
- Preferred - Knowledge of the insurance industry and its data requirements.
- Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
- Excellent communication and problem-solving skills to work effectively with diverse teams
- Excellent problem-solving skills and ability to work under tight deadlines.
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