IN_Associate AWS Data Engineer Data And Analytics Advisory Kolkata

PwC; Kolkata District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

PwC is seeking an experienced AWS Data Engineer to design, build, and optimize scalable data ingestion and ETL/ELT pipelines. You will leverage SQL, Python, and PySpark to transform raw data into actionable insights for clients, with a focus on production readiness and high-volume processing.

Responsibilities include deploying AWS Glue, Step Functions, Lambda, and DMS, implementing reliable data pipelines, ensuring data integrity, and enabling timely EOD loads.

Qualifications

• Expert-level SQL development and performance optimization.
• Strong proficiency in SQL, Python, and PySpark.
• Hands-on experience with ETL pipelines and orchestration frameworks.
• Solid understanding of ACID-compliant data ingestion principles.
• Experience with schema evolution and CDC (Change Data Capture) patterns.
• Experience owning production readiness and end-to-end solution delivery.
• Exposure to cloud-native architectures and AWS tools such as Glue, Step Functions, Lambda, and DMS.

Responsibilities

• Develop ETL/ELT pipelines using AWS services such as Glue, Step Functions, Lambda, and DMS.
• Implement direct-to-Aurora ingestion strategies for snapshots and delta loads.
• Ensure referential integrity, correct processing order, idempotency, and recovery mechanisms.
• Build monitoring, validation, and reconciliation frameworks for production data pipelines.
• Manage scalability and throughput during high-volume EOD ingestion workloads.

Skills

SQL

Python

PySpark

ETL pipelines

ACID ingestion

Schema evolution & CDC

Production readiness

AWS data services

Education

BE/B.Tech

MBA

MCA

Tools

AWS Glue

AWS Step Functions

AWS Lambda

AWS DMS

PostgreSQL (distributed)

Kafka

Job description

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Associate

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

Why PWC

At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes forour clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences foreach other.

Learn more about us.

At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations.

Job Description & Summary

We are looking for an experienced AWS Data Engineer with strong expertise in SQL, Python, and PySpark to design, build, and optimize scalable data ingestion and ETL/ELT pipelines. The role requires hands-on experience with AWS services such as Glue, Step Functions, Lambda, and DMS, along with a strong understanding of data engineering best practices, production readiness, and high-volume data processing.

Responsibilities:

• Develop ETL/ELT pipelines using AWS services such as Glue, Step Functions, Lambda, and DMS.

• Implement direct-to-Aurora ingestion strategies for snapshots and delta loads.

• Ensure referential integrity, correct processing order, idempotency, and recovery mechanisms.

• Build monitoring, validation, and reconciliation frameworks for production data pipelines.

• Manage scalability and throughput during high-volume EOD ingestion workloads.

Mandatory skill sets:

• Expert-level SQL development and performance optimization.

• Strong proficiency in SQL, Python, and PySpark.

• Hands-on experience with ETL pipelines and orchestration frameworks.

• Solid understanding of ACID-compliant data ingestion principles.

• Experience with schema evolution and CDC (Change Data Capture) patterns.

• Experience owning production readiness and end-to-end solution delivery.

• Exposure to cloud-native architectures and AWS tools such as Glue, Step Functions, Lambda, and DMS.

Preferred skill sets:

• Experience with SAP ODP or enterprise data replication technologies.

• Familiarity with distributed PostgreSQL systems.

• Exposure to event-driven architectures such as Kafka.

Years of experience required:

Experience: 5–8 years

• Minimum 3 years of relevant work experience, typically reflecting 5+ years in data engineering, data integration, or related roles.

• Proven track record of building resilient and idempotent ingestion frameworks.

• Experience supporting high-volume, time-sensitive processing, especially EOD workloads.

• Strong operational mindset, including monitoring, alerting, and maintaining runbooks.

Education Qualification:

BE, B.Tech, ME, M.Tech, MBA, MCA or equivalent qualification preferred

Degrees/Field of Study required: MBA (Master of Business Administration), Bachelor of Technology, Bachelor of EngineeringDegrees/Field of Study preferred:

Education (if blank, degree and/or field of study not specified)

Certifications

(if blank, certifications not specified)

Required Skills

Amazon Web Services (AWS), Data Engineering

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Data Anonymization, Data Architecture Development, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline, Data Quality, Data Strategy {+ 22 more}

Desired Languages

(If blank, desired languages not specified)

Job Posting End Date

August 24, 2026