Capco - Data Engineer - Scala (5-9 yrs)

Job Title : Data Engineer Scala.

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 : Data Engineer Scala.

Location : Bangalore.

Experience : 5 to 9 years.

Role Description :

We are seeking a highly skilled and experienced Data Engineer with a strong foundation in Scala, Spark, Hadoop, and Hive to join our growing team. In this role, you will be responsible for designing, developing, and maintaining robust and scalable data pipelines to support our data-driven initiatives. You will work closely with data scientists, analysts, and business stakeholders to understand their data needs and translate them into effective and efficient data solutions.

Key Responsibilities :

- Design, develop, and maintain high-performance data pipelines using Spark, Hadoop, and Hive.

- Develop and implement data ingestion, transformation, and loading (ETL) processes for large volumes of data.

- Optimize data processing performance and reduce data latency.

- Work with data scientists and analysts to understand their data requirements and translate them into effective data solutions.

- Collaborate with cross-functional teams to ensure data quality and integrity.

- Implement and maintain data quality checks and monitoring systems.

- Participate in all phases of the software development lifecycle, including design, development, testing, and deployment.

- Stay updated on the latest advancements in data engineering technologies and best practices.

Required Skills :

Must Have :

- Strong hands-on experience with Spark, Hadoop, and Hive.

- Proficiency in Python, PySpark, and Scala.

Should Have :

- Experience working with semi-structured and large volumes of data.

- Good understanding of CI/CD pipelines.

- Knowledge of any scheduling tool (e.g., Airflow, Oozie).

- Familiarity with data warehousing concepts.

Desired Skills :

- Experience with cloud platforms such as AWS, Azure, or GCP.

- Knowledge of containerization technologies such as Docker and Kubernetes.

- Experience with stream processing technologies such as Kafka or Flink.

- Experience with NoSQL databases such as Cassandra or MongoDB.

- Strong communication and collaboration skills.

- Ability to work independently and as part of a team.