Senior Data Engineer, Director

NatWest Group; Gurugram District; On-site; INR 1,400,000 - 2,400,000; Full time

Job summary

NatWest Group is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines and architectures that empower analytics and reporting across the bank.

The role emphasizes real-time data processing with Spark Streaming, Flink, and AWS data services, along with collaboration with data scientists and analytics teams. A senior, leadership-capable profile is expected.

Qualifications

• 12+ years of professional Data Engineer experience.
• Strong expertise in Apache Spark (including Spark Streaming) and real-time processing.
• Proficient in Scala, Python, and Flink for data pipelines.

Responsibilities

• Design, build and maintain scalable data pipelines and architectures.
• Develop data lake/warehouse architectures and data models for analytics.
• Mentor junior engineers and collaborate with data scientists and analysts.

Skills

Strong communication

Stakeholder management

Data modeling

ETL design

Leadership potential

Education

Bachelor's or Master's in CS/Engineering/IS

Tools

Apache Spark

Spark Streaming

Apache Flink

Scala

Python

FastAPI

AWS (EMR, Kinesis, DynamoDB, Athena, QuickSight)

Parquet

Iceberg

Docker

Podman

Kubernetes

PostgreSQL

Hive

SQL

Job description

Join us as a Senior Data Engineer

• We'll look to you to drive the build of effortless, digital-first customer experiences as you simplify our bank while keeping our data safe and secure
• Day-to-day, you'll develop innovative, data-driven solutions through data pipeline modelling and ETL design, inspiring to be commercially successful through insights
• This is your opportunity to explore your leadership potential while bringing a competitive edge to your career profile by solving problems and creating smarter solutions
• We're offering this role at director level

What you'll do

In this role, you'll design, build and maintaining scalable data pipelines and architectures. The ideal candidate will have strong expertise in handling large data sets, optimising data flows, and collaborating closely with data scientists, analysts, and other engineering teams to enable data-driven decision-making.

We'll look to you to design, develop, and maintain scalable data pipelines and ETL processes to support analytics and reporting requirements, while building and optimizing data architectures including data lakes, data warehouses, and databases. You'll develop and support real-time data streaming applications using Apache Spark Streaming and Apache Flink, perform Spark performance tuning for large-scale data processing, and collaborate closely with data scientists and analysts to deliver clean, reliable, and high-quality datasets.

You'll also be responsible for:

• Driving customer value by understanding complex business problems and requirements to correctly apply the most appropriate and reusable tools to gather and build data solutions
• Ensureing data quality, integrity, and security across all data platforms.
• Implementing best practices for data governance and compliance.
• Monitoring and troubleshooting data pipeline performance and resolve data-related issues proactively.
• Evaluating and integrating new data technologies and tools to enhance data processing capabilities, with a focus on AI tools and concepts.
• Collaborating with cross-functional teams to support data-driven initiatives.
• Mentoring and guiding junior data engineers and team members.

The skills you'll need

We're looking for someone with strong communication skills and the ability to proactively engage and manage a wide range of stakeholders. You'll need at least twelve years of professional experience as a Data Engineer or in a similar role, with strong expertise in Apache Spark including Spark Streaming and performance optimization, Scala, Python, and Apache Flink for real-time data processing. You'need expertise in AI concepts and tools within data engineering workflows, build high-performance data APIs using FastAPI, and working extensively with AWS services such as EMR, Kinesis, DynamoDB, Athena, and QuickSight.

You'll need hands-on experience with data lake technologies and formats including Parquet and Apache Iceberg, containerization platforms such as Docker and Podman, and relational databases including PostgreSQL and Hive, supported by strong SQL skills. You'll also contribute to machine learning pipeline integration, ensure compliance with GDPR and other data privacy regulations, and hold a Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field.

You'll also need:

• Expertise inETL tools and frameworks and data pipeline orchestration.
• Strong understanding of cloud data platforms and services.
• Knowledge of data modelling, schema design, and data architecture principles.
• Familiarity with data security standards and compliance requirements.
• Experience with DevOps, CI/CD pipelines, and container orchestration like Kubernetes
• An understanding of modern code development practices