๐ Job Overview
EXL is hiring experienced professionals for AWS Data Engineer and AWS Lead Data Engineer positions across multiple Indian locations.
- ๐ข Company: EXL
- ๐ผ Job Titles: AWS Data Engineer / AWS Lead Data Engineer
- ๐ Job Locations: Gurugram, Pune, Bangalore
- โณ Experience Required: 5+ years for AWS Data Engineer; 8+ years for AWS Lead Data Engineer
- โ๏ธ Cloud Platform: Amazon Web Services (AWS)
- ๐๏ธ Database Technology: Snowflake and SQL
- ๐ป Programming Languages: Python
- โ๏ธ Big Data Technology: PySpark
- ๐ Preferred Notice Period: Candidates with 60โ90 days’ notice period will be preferred
- ๐ Educational Qualification: Not specified in the announcement
- ๐ข Work Mode: Not specified
- ๐ Employment Type: Not specified
- ๐ฐ Salary: Not disclosed
- ๐ Job ID: Not provided
- ๐ฅ Eligible Candidates: Experienced data engineering professionals from reputed organizations with relevant technical expertise
- ๐ฉ Application Method: Share your updated resume through the recruiter email addresses mentioned below.
๐ ๏ธ Key Responsibilities
The announcement does not provide a detailed responsibility list. However, based on the specified technologies and job titles, candidates should be prepared for responsibilities typically associated with these positions:
- โ๏ธ AWS Data Engineering: Design, develop, and maintain cloud-based data processing and integration solutions using AWS services.
- ๐๏ธ Data Warehousing: Work with Snowflake to organize, transform, and manage structured data for analytical requirements.
- ๐ Python Development: Develop reusable scripts and data processing components using Python.
- โก Big Data Processing: Use PySpark for distributed data processing and handling large datasets.
- ๐ SQL Development: Write and optimize complex SQL queries for data transformation and extraction.
- ๐ค Stakeholder Management: Understand business requirements, communicate technical solutions, and coordinate with stakeholders.
- ๐จโ๐ป Technical Leadership: Lead-level candidates may be expected to guide engineering activities, review solutions, and support team delivery.
๐ Why Is This Role a Good Opportunity?
This opportunity is relevant for experienced IT professionals looking to strengthen their careers in cloud-based data engineering.
- ๐ Cloud Technology Exposure: Work involving AWS can help professionals deepen their understanding of cloud infrastructure and data engineering architecture.
- ๐ Modern Data Stack: The combination of Snowflake, Python, SQL, and PySpark represents an important technology stack in contemporary data engineering.
- ๐ข Enterprise Experience: Candidates can explore opportunities involving enterprise-level data solutions and business requirements.
- ๐ Career Progression: Professionals with 8+ years of experience can consider the lead position to pursue technical leadership and stakeholder management responsibilities.
- ๐ค Business Communication: The emphasis on stakeholder management provides an opportunity to apply technical knowledge in business-facing environments.
๐ง Skills Required
โ๏ธ Core Technical Skills
- โ๏ธ AWS: Practical experience with AWS cloud services and data engineering workflows.
- ๐๏ธ Snowflake: Knowledge of data warehousing, SQL transformations, and query optimization.
- ๐ป SQL: Strong command of joins, subqueries, CTEs, window functions, and performance optimization.
- ๐ Python: Experience writing scripts, handling datasets, and implementing data processing logic.
- โก PySpark: Understanding of DataFrames, transformations, actions, partitions, and distributed processing.
โ๏ธ Professional Skills - ๐ค Strong stakeholder management capabilities.
- ๐ฃ๏ธ Excellent verbal and written communication.
- ๐งฉ Problem-solving and analytical thinking.
- ๐ฅ Ability to collaborate with technical and business teams.
- ๐ฏ For lead candidates, technical guidance and coordination skills are particularly relevant.
๐ค Expected Interview Rounds
The exact EXL interview process has not been confirmed in the announcement. The following stages are indicative preparation suggestions:
- ๐ Round 1 โ Recruiter Screening: Discussion about current experience, notice period, preferred location, salary expectations, and technical background.
- ๐ป Round 2 โ Technical Interview: Questions on AWS, Python, SQL, Snowflake, PySpark, ETL pipelines, and data engineering concepts.
- โ๏ธ Round 3 โ Practical or Scenario-Based Assessment: Possible SQL queries, Python coding exercises, PySpark transformations, or cloud data pipeline scenarios.
- ๐๏ธ Round 4 โ Architecture and Project Discussion: Discussion of previous data engineering projects, pipeline design, optimization, troubleshooting, and production challenges.
- ๐จโ๐ผ Round 5 โ Managerial Discussion: Particularly relevant for lead candidates, covering stakeholder management, technical decision-making, team collaboration, and delivery ownership.
- ๐ค Final HR Discussion: Compensation, availability, joining timeline, and other employment details.
๐ฐ Expected Salary Range
๐ Preparation Tips for This Specific Job
Candidates should concentrate on practical implementation and real-world data engineering scenarios.
- โ๏ธ Revise AWS: Prepare AWS data engineering concepts, including S3, Glue, Lambda, Redshift, IAM, and data pipeline architecture.
- ๐๏ธ Practice Snowflake: Understand virtual warehouses, stages, file formats, streams, tasks, and query optimization.
- ๐ป Strengthen SQL: Practice complex joins, ranking functions, window functions, CTEs, aggregations, and query performance scenarios.
- ๐ Work on Python: Revise dictionaries, lists, functions, exception handling, file operations, and data manipulation.
- โก Practice PySpark: Understand DataFrames, transformations, actions, joins, partitioning, caching, and handling large datasets.
- ๐๏ธ Prepare Project Scenarios: Be ready to explain an end-to-end ETL pipeline, source-to-target mapping, data quality checks, error handling, and production troubleshooting.
- ๐ค Prepare for Lead Responsibilities: Experienced candidates should demonstrate architecture decisions, stakeholder communication, mentoring, and delivery management through genuine examples.
๐ Resume Tips
A well-structured, ATS-friendly resume can help recruiters identify relevant experience quickly.
- ๐ Highlight AWS, SQL, Snowflake, Python, and PySpark prominently in the technical skills section.
- ๐๏ธ Include relevant cloud data engineering and ETL pipeline projects.
- ๐ Mention measurable achievements, such as improvements in processing time, query performance, or pipeline reliability, only when supported by actual results.
- ๐ป Explain your individual contributions rather than listing only team responsibilities.
- โ๏ธ Mention specific AWS services you have genuinely used in production.
- ๐จโ๐ผ For lead roles, highlight architecture ownership, technical mentoring, stakeholder coordination, and project delivery.
- ๐ Clearly mention your current notice period and realistic availability.
- ๐ฏ Tailor your professional summary to the AWS Data Engineer or AWS Lead Data Engineer position.
๐ฉ How to Apply
Interested and eligible candidates can share their updated resumes through the recruiter email addresses provided in the original hiring announcement.
๐ง Recruiter Email Addresses:
- ๐ฉ vibhakar.verma@exlservice.com
- ๐ฉ Garima.awasthi@exlservice.com
- ๐ฉ vivek.sahni@exlservice.com
๐ Application Instructions:
- ๐ Mention the position title in your email subject.
- ๐ Clearly specify your preferred location: Gurugram, Pune, or Bangalore.
- โณ Include your total experience and notice period.
- ๐ป Attach your updated resume highlighting AWS, SQL, Snowflake, Python, and PySpark experience.
- ๐ค Ensure that your experience aligns with the 5+ years or 8+ years requirement.
Note: The hiring announcement does not provide a separate application URL. Candidates should use the recruiter email addresses above and verify the opportunity before sharing personal information.
๐ Final Thoughts
EXL’s hiring for AWS Data Engineers and AWS Lead Data Engineers is a relevant opportunity for experienced professionals with strong cloud data engineering skills. Candidates with hands-on experience in AWS, Snowflake, SQL, Python, and PySpark should consider applying if their experience matches the requirements.
Professionals targeting the lead position should also demonstrate strong technical ownership, stakeholder management, and communication skills.
๐ Prepare your updated resume, highlight your real-world project experience, and connect with the recruiters through the verified email addresses provided in the hiring announcement.
