Data Engineer with DataBricks

Capco

Pune, India

On-siteCareer-pivot friendly

Who this role is best for

Strong fit for data engineers who build scalable data pipelines and work with cloud-based platforms, particularly those with experience in Databricks and Spark.

Best fit for

Candidates with 5+ years of experience in building data pipelines on Databricks and Spark
— “5+ years of experience in Data Engineering.”
Professionals adept at optimizing big data workloads and handling structured, semi-structured, and unstructured data
— “Developing batch and streaming data pipelines, optimizing big data workloads.”
Individuals with a background in ETL/ELT frameworks and cloud data platforms
— “Experience with ETL/ELT frameworks and data integration.”

Things to consider

The role requires full-time commitment and may involve on-site work in Pune
— “Employment Type: Full-Time”
Candidates must be prepared for a collaborative environment with Data Architects and Data Scientists
— “Collaborate with Data Architects, Business Analysts, and Data Scientists to understand and implement data requirements.”

How to stand out

Highlight experience with Databricks Lakehouse Platform and Delta Lake in your resume
— “Build and optimize ETL/ELT processes on the Databricks Lakehouse Platform.”
Demonstrate your ability to design and maintain data lakes and warehouses
— “Design and maintain data models, data lakes, and data warehousing solutions.”
Showcase your track record in performance tuning of Spark workloads
— “Perform performance tuning and optimization of Spark workloads.”
Emphasize your experience with cloud platforms like Azure Databricks and AWS Databricks
— “Experience working with cloud platforms such as: Azure Databricks, AWS Databricks, GCP Databricks.”
Include examples of data governance and security implementation in your application
— “Implement data quality, governance, and security standards.”

Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

design, develop, and maintain scalable data pipelines
build and optimize ETL/ELT processes

Typical background

data engineeringsoftware engineeringdata science

Skills & requirements

Required

PythonScalaDatabricksApache SparkETLData WarehousingCloud Platforms

Preferred

Data QualityData GovernanceData Security

Stack & domain

PythonScalaSparkDatabricksDelta LakeEtl/eltData WarehousingCloud PlatformsCollaborationProblem-solvingCommunicationBankingFinancial ServicesEnergy

About the role

Original posting from Capco via Greenhouse

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.
MAKE AN IMPACT
Job Title: Data Engineers
Location: Pune, Maharashtra
Experience: 5+ Years
Employment Type: Full-Time
About the Role
We are looking for a skilled Data Engineer with strong expertise in Python, Scala, and Databricks to build and maintain scalable data processing solutions. The ideal candidate should have hands-on experience in developing batch and streaming data pipelines, optimizing big data workloads, and working in cloud-based data platforms.
Key Responsibilities
Design, develop, and maintain scalable data pipelines using Python, Scala, and Spark.
Build and optimize ETL/ELT processes on the Databricks Lakehouse Platform.
Develop high-performance data processing solutions for large-scale datasets.
Work with structured, semi-structured, and unstructured data sources.
Collaborate with Data Architects, Business Analysts, and Data Scientists to understand and implement data requirements.
Perform performance tuning and optimization of Spark workloads.
Design and maintain data models, data lakes, and data warehousing solutions.
Implement data quality, governance, and security standards.
Troubleshoot production issues and support data platform operations.
Participate in Agile ceremonies, code reviews, and technical design discussions.
Required Skills
Technical Skills
5+ years of experience in Data Engineering.
Strong programming skills in Python and Scala.
Hands-on experience with Databricks and Apache Spark.
Expertise in Spark SQL, DataFrames, Delta Lake, and Databricks Workflows.
Strong SQL development and query optimization experience.
Experience with ETL/ELT frameworks and data integration.
Good understanding of Data Warehousing concepts and dimensional modeling.
Experience working with cloud platforms such as:
Azure Databricks
AWS Databricks
GCP Databricks
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.

Source: Capco careers (Greenhouse)