EXL is hiring experienced Data Engineers for opportunities in Gurugram and Bengaluru, with 6+ years of experience required and immediate joiners preferred. The detailed job description is strongly focused on Databricks, Azure Cloud, PySpark, Python, SQL, Azure Data Factory, Azure Data Lake, Delta Lake and modern data engineering practices.
Important: The opening headline mentions βCloud Engineerβ and βFull Stack Engineer,β but the detailed responsibilities and candidate profile clearly describe a Data Engineer position. This article therefore focuses on the detailed Data Engineer β Databricks/Azure requirements.
π Job Details
- π’ Company: EXL
- πΌ Role: Data Engineer
- π― Experience: 6β10 Years
- π Locations: Gurugram / Bengaluru
- β±οΈ Joining: Immediate Joiners Only
- βοΈ Cloud: Microsoft Azure
- β‘ Core: Databricks, PySpark, Python, SQL
- π Data: ETL/ELT, Data Modeling, Delta Lake, Data Warehousing
- π οΈ Azure Tools: Azure Data Factory, Azure Databricks, Azure Data Lake
- π Advanced: Delta Live Tables, Auto Loader, Unity Catalog
- π¦ Preferred Domain: Insurance
- π© Apply: Swati.Srivastava1@exlservice.com
π’ About EXL
EXL Official Website is a global data and AI company that helps enterprises use data, analytics, AI and digital technologies to improve business outcomes. EXL works across industries including insurance, healthcare, banking and capital markets, retail, communications, and energy & infrastructure. The company currently has approximately 67,000 employees across six continents.
EXL has particularly strong capabilities in data and analytics. Its official site highlights data management, advanced analytics, AI, cloud and industry-specific solutions, making this Data Engineering opportunity highly relevant for professionals wanting to work on enterprise-scale data platforms.
β Why This Role Is Excellent for Experienced Data Engineers
This is more than a pipeline-development role. At 6β10 years of experience, candidates are expected to take ownership of data platforms, improve reliability, mentor engineers and participate in technical decision-making.
The role combines Azure + Databricks + PySpark + Delta Lake + data governance + performance engineering, giving candidates exposure to the complete modern data engineering lifecycle. You would work on scalable ingestion and transformation, data quality, observability, performance optimization and enterprise governance.
The insurance preference is another advantage. EXL has significant industry expertise in insurance, and its data and analytics services specifically support insurance-related businesses.
π οΈ Skills Required
Candidates should have strong hands-on experience with:
- π Python & PySpark: Data transformation, functions, DataFrames, joins, window functions and Spark optimization.
- ποΈ SQL: Complex joins, CTEs, window functions, query optimization, aggregations and data validation.
- β‘ Databricks: Workflows, clusters, notebooks, Delta tables, performance optimization and job orchestration.
- βοΈ Azure: ADF, ADLS/ADLS Gen2, Azure Databricks, storage and security concepts.
- π ETL/ELT: Incremental loads, full loads, CDC, error handling, retries and data-quality checks.
- 𧱠Delta Lake: ACID transactions, MERGE, OPTIMIZE, VACUUM, partitioning and schema evolution.
- π Unity Catalog: Data governance, permissions, catalogs, schemas, lineage and secure data access.
- π Advanced Databricks: Delta Live Tables and Auto Loader.
- π Data Modeling: Star schema, dimensional modeling, fact/dimension tables and SCD Type 1/2.
π― Expected EXL Interview Rounds
EXL does not publish one fixed interview structure for this specific vacancy, so the exact process can vary by team and client. Recent candidate reports for EXL Azure/Data Engineering roles indicate technical interviews covering SQL, Python, cloud, Databricks, PySpark and ADF, followed by managerial and client discussions.
A realistic process may include:
- Round 1 β Technical Screening: SQL, Python/PySpark, Azure and project experience.
- Round 2 β Advanced Technical: Databricks, Spark optimization, Delta Lake, ADF, data modeling and architecture.
- Round 3 β Managerial/Leadership: Ownership, mentoring, stakeholder management, problem-solving and delivery scenarios.
- Round 4 β Client/Final Discussion: Business requirements, communication, domain knowledge and project-specific technical scenarios.
For senior candidates, be prepared to explain why you selected a particular architecture, not merely what technology you used.
π° Expected Salary Range
The job announcement does not provide an official salary range. Current third-party data for EXL Senior Data Engineers with 5β9 years of experience reports approximately βΉ21.6β35 LPA, based on employee-reported salary data.
Therefore, for a strong 6β10 year candidate with Databricks, Azure, PySpark and architecture experience, a practical target could be around βΉ20β35+ LPA, depending on current CTC, technical depth, role level and negotiation. This is a market estimate, not an official EXL salary band.
π Preparation Tips
π₯ Databricks: Be ready to explain cluster types, Spark architecture, partitioning, caching, AQE, OPTIMIZE, Z-ORDER, VACUUM and Delta Lake internals.
β‘ PySpark: Practice joins, repartition vs. coalesce, broadcast joins, window functions, handling skew and optimizing large datasets.
βοΈ ADF: Revise linked services, datasets, pipelines, triggers, integration runtime, parameterization, incremental loads and failure handling.
𧱠Delta Lake: Prepare MERGE, schema evolution, time travel, Change Data Feed, OPTIMIZE and transaction logs.
π Auto Loader/DLT: Understand incremental ingestion, schema evolution, expectations, data quality and pipeline orchestration.
π Unity Catalog: Know catalogs, schemas, external locations, permissions, lineage and governance.
π Performance: Prepare a real example where you reduced pipeline execution time or cloud compute cost.
π¦ Insurance: Learn basic concepts such as policies, claims, premiums, customers, coverage and transactions, and think about how these datasets would move through an enterprise data platform.
π Resume Tips for This Role
Your resume headline should immediately communicate: Senior Data Engineer | Azure | Databricks | PySpark | Python | SQL | Delta Lake.
Put Databricks, Azure Data Factory, ADLS, PySpark, Delta Lake and Unity Catalog near the top rather than burying them in a large skills section.
For each project, quantify your impact. Instead of writing βDeveloped ETL pipelines,β write: βDesigned and optimized PySpark/Databricks pipelines processing 500GB+ daily data, reducing processing time by 40%.β
Highlight pipeline performance tuning, data-quality frameworks, monitoring, governance, mentoring and architecture ownership because these directly match the senior-level responsibilities in the JD.
If you have insurance experience, explicitly mention the business workflows and datasets you worked with.
π How to Apply
Interested candidates should send their profile summary and updated resume to:
π© Swati.Srivastava1@exlservice.com
Mention the following in your email:
- Total Experience: 6+ Years
- Primary Skills: Databricks, Azure, PySpark, Python, SQL
- Current Location
- Preferred Location: Gurugram/Bengaluru
- Notice Period: Immediate Joiner
- Relevant Insurance Experience: If applicable
