Data Engineer Scala + Spark + Java (Bng & Pune)

About Us

Capco a Wipro company is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe we support 100 clients acrossbanking financial and Energy sectors. We are recognized for our deep transformation execution and delivery.

WHY JOIN CAPCO

You will work on engaging projects with the largest international and local banks insurance companies payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant open culture that values diversity inclusivity and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco everyone has the opportunity to grow as we grow taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

MAKE AN IMPACT

Job Title: Data Engineer

Position: Data Engineer
Location: (Pune & Bengaluru preferred)
Experience: 5 Years
Work Mode: Hybrid (Capco Office)

Key Responsibilities

• Design develop and optimize large-scale data processing applications using Scala Apache Spark and Java.
• Build and maintain high-performance data pipelines capable of processing 8090 million records daily with a focus on scalability reliability and efficiency.
• Develop and integrate Native APIs and data services to support business-critical applications and analytics platforms.
• Collaborate with cross-functional teams to gather requirements and deliver robust data engineering solutions.
• Optimize Spark jobs data workflows and distributed computing processes to ensure high throughput and low latency.
• Implement best practices for data quality monitoring governance and operational excellence.
• Troubleshoot and resolve performance bottlenecks across data processing and ingestion pipelines.
• Participate in code reviews and contribute to engineering standards architecture decisions and continuous improvement initiatives.

Required Skills & Experience

• Strong hands-on experience in Scala Apache Spark and Java.
• Proven experience building and supporting large-scale distributed data processing systems handling tens of millions of records daily.
• Expertise in developing and consuming Native APIs and microservices.
• Strong understanding of Spark architecture performance tuning partitioning caching and optimization techniques.
• Experience with data modeling ETL/ELT processes and large-scale batch and streaming data pipelines.
• Solid understanding of distributed systems concurrency and high-volume data processing.
• Experience with SQL and relational/non-relational databases.
• Strong debugging analytical and problem-solving skills.

Preferred Qualifications

• Experience working in enterprise-scale data environments within Financial Services Payments or FinTech domains.
• Exposure to cloud platforms (AWS Azure or GCP) and containerized deployments.
• Familiarity with Kafka Airflow Hadoop ecosystem or similar big data technologies.
• Experience with CI/CD pipelines DevOps practices and Agile methodologies.

What Were Looking For

• Engineers passionate about solving complex data challenges at scale.
• Professionals who can design highly performant systems capable of processing and transforming massive datasets efficiently.
• Team players who thrive in fast-paced collaborative environments and take ownership of end-to-end delivery.