Job Title: Data Engineers
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 across banking, 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.
Job Title: Senior Data Engineer (Kafka)
Experience: 5+ Years
Location: Pune (Preferred)
Employment Type: Full-Time
We are looking for an experienced Senior Data Engineer with strong expertise in Apache Kafka, Apache Spark, Scala/PySpark, SQL, and modern data engineering technologies. The ideal candidate should have hands-on experience designing, developing, optimizing, and maintaining scalable data pipelines, including batch and real-time streaming solutions.
The role requires strong technical expertise, problem-solving abilities, production support experience, and the capability to independently deliver complex data engineering solutions while mentoring junior team members.
Key Responsibilities- Design, develop, and maintain scalable, reliable, and high-performance data pipelines for batch and real-time data processing.
- Implement and optimize Kafka-based event streaming solutions, ensuring reliable data ingestion, processing, and integration.
- Develop production-grade data processing applications using Apache Spark and Scala/PySpark.
- Optimize Spark workloads through effective partitioning, caching, skew handling, join optimization, and performance tuning.
- Write advanced SQL queries involving complex joins, window functions, data transformations, and query optimization.
- Design, develop, and troubleshoot ETL/ELT workflows using Apache NiFi, Apache Airflow, or Azure Data Factory (ADF).
- Work with cloud-based data storage solutions such as Amazon S3, Azure Data Lake Storage (ADLS), and Data Lakes.
- Develop Python scripts, automation utilities, reusable ETL components, and testing frameworks.
- Monitor and support production data pipelines, troubleshoot incidents, perform root cause analysis (RCA), and implement preventive measures.
- Design end-to-end data engineering solutions with a focus on scalability, performance, reliability, and maintainability.
- Conduct code reviews, enforce engineering best practices, and mentor junior data engineers.
1. Apache Kafka / Event Streaming
- Strong understanding of Kafka architecture, event streaming concepts, and implementation.
- Hands-on experience developing and supporting Kafka-based data ingestion and streaming pipelines.
- Knowledge of Kafka producers, consumers, topics, partitions, consumer groups, and offset management.
- Understanding of fault tolerance, message delivery guarantees, and streaming performance optimization.
2. Apache Spark
- Strong hands-on experience with Apache Spark for large-scale data processing.
- Expertise in Spark performance tuning, including joins, partitioning, caching, data skew handling, and troubleshooting.
- Experience developing and optimizing production-grade Spark applications.
3. Scala / PySpark
- Strong proficiency in at least one of Scala or PySpark, with working knowledge of the other.
- Ability to write efficient, maintainable, and production-ready code.
4. SQL
- Advanced SQL skills, including complex joins, window functions, query optimization, and data modeling.
- Experience working with large datasets and optimizing SQL performance.
5. Data Orchestration – NiFi / Airflow / ADF
- Strong experience in at least one orchestration tool, with working knowledge of the others.
- Ability to independently design, develop, monitor, and troubleshoot data pipelines.
6. Cloud Storage – S3 / ADLS / Data Lake
- Experience working with cloud-based data lakes and storage solutions.
- Understanding of file formats, partitioning strategies, storage design, data lifecycle management, and performance considerations.
7. Python
- Good Python scripting and automation skills.
- Experience building utilities, ETL components, and automated testing frameworks.
8. Production Support & Troubleshooting
- Experience handling production incidents, monitoring data pipelines, and performing root cause analysis.
- Ability to implement resiliency improvements and ensure pipeline stability.
- Ability to independently design and deliver medium-to-complex data engineering pipelines with minimal guidance.
- Strong analytical, debugging, and problem-solving skills.
- Good understanding of data engineering best practices, performance optimization, and scalable architecture.
- Experience conducting code reviews and mentoring junior engineers.
- Strong communication and collaboration skills.
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline.
- Minimum 5+ years of relevant experience in data engineering, big data technologies, and data pipeline development.
- Hands-on experience with Kafka-based streaming solutions and distributed data processing frameworks.
We are seeking a technically strong, hands-on Senior Data Engineer who can independently own data engineering deliverables, build robust Kafka-based streaming pipelines, optimize large-scale Spark workloads, resolve complex production issues, and contribute to technical design decisions.
If you are keen to join us, you will be part of an organization that values your contributions, recognizes your potential, and provides ample opportunities for growth. For more information, visit www.capco.com. Follow us on Twitter, Facebook, LinkedIn, and YouTube.
Skills Required
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related discipline
- 5+ years of relevant experience in data engineering, big data technologies, and data pipeline development
- Hands-on experience with Apache Kafka-based streaming solutions
- Strong hands-on experience with Apache Spark and Spark performance tuning
- Strong proficiency in Scala or PySpark, with working knowledge of the other
- Advanced SQL skills, including complex joins, window functions, query optimization, and data modeling
- Experience with at least one of Apache NiFi, Apache Airflow, or Azure Data Factory
- Experience with cloud-based data lakes and storage such as Amazon S3 or Azure Data Lake Storage
- Good Python scripting and automation skills
- Production support, pipeline monitoring, incident troubleshooting, and root cause analysis experience
- Ability to independently design and deliver medium-to-complex data engineering pipelines
- Experience conducting code reviews and mentoring junior engineers
- Strong analytical, debugging, problem-solving, communication, and collaboration skills
What the Team is Saying
Capco Compensation & Benefits Highlights
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Healthcare Strength — Health insurance is described as comprehensive with multiple plan options and generally low copays, and mental-health support and EAP resources reinforce this strength.
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Leave & Time Off Breadth — Paid time off, holidays, and sick leave are often highlighted as generous, with flexible time-off arrangements supporting work-life balance.
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Parental & Family Support — Parental leave is characterized as generous, and family-planning benefits such as fertility, adoption assistance, childcare support, and coverage for family members are emphasized.
Capco Insights
What We Do
Capco, a Wipro company, is a global management and technology consultancy specializing in driving transformation in the energy and financial services industries. Capco operates at the intersection of business and technology by combining innovative thinking with unrivalled industry knowledge to fast-track digital initiatives for banking and payments, capital markets, wealth and asset management, insurance, and the energy sector. Capco’s cutting edge ingenuity is brought to life through its award-winning Be Yourself At Work culture and diverse talent. TRUSTED ADVISORS - Our collaborative and entrepreneurial approach position us as trusted long-term partners to our clients. DEEP EXPERTISE - Clients look to us for clear guidance, proven expertise, and the support they need to set their companies up for success. DISRUPTIVE SOLUTIONS- We do not provide off -the-shelf answers to clients’ challenges. Instead, we work in close collaboration to understand the issues, and craft disruptive, bespoke solutions. ACCOUNTABILITY AND OWNERSHIP - We recognize every client has distinct needs and expectations, and we take ownership and accountability for the solutions we design, build, and deliver.
Why Work With Us
We support and encourage an inclusive culture, entrepreneurial outlook and independent thinking. Capco is not about organizational charts and rigid hierarchies – we want all employees to feel that Capco is their firm to own and run. We believe diversity powers innovation. Be Yourself At Work (#BYAW) is an integral and underlying part of our culture
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Capco Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
