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Mumbai · On-site · 5-8 Yrs · Sep 23
Accounting & Tax · 10000+ Employees · New York, US
9 open roles4 posted in 7d9 in 30d
Work-life balance 2.9Compensation & benefits 3.3Culture & values 3.5
Hiring: Engineering
What employees say
+ You get to learn a lot there, and I had an opportunity to work in the client location.
− Career and financial growth is slower.
More reviews on the company profile.
Interview experience · Summer Associate
2 interviews and an HR round Had one case interview and one interview about Indian defense Policy and strategy The case interview had 2 parts with one small presentaion towards the end The HR round was standart more l
Average difficulty · Bengaluru · 2,675 reports
More interview insightsJob description
Overview
AdvisoryIndustry/Sector
Responsibilities
- Position: Data Engineering / Senior Associate
- Design, develop, and maintain scalable data pipelines and architectures using Spark, PySpark, and Python.
- Lead and manage a team of data engineers, providing technical guidance, mentorship, and performance management.
- Collaborate with cross-functional teams to understand data requirements and deliver high-quality data solutions.
- Ensure data quality, integrity, and security across all data engineering projects.
- Implement best practices for data engineering, including code reviews, testing, and documentation.
- Stay up-to-date with the latest industry trends and technologies in data engineering and cloud computing.
- Work closely with stakeholders to understand business needs and translate them into technical requirements.
- Manage project timelines, resources, and budgets to ensure successful delivery of data engineering projects.
Qualifications
- Location: Mumbai
- Type: Full Time
- Certifications: Spark 3.0(Mandatory) and/or Databricks Advanced/Professional Architect.
- About the Role
- We are seeking an experienced and Senior Associate with 5-8 years of experience specializing in data services, data architecture, and data platforms to lead our Data engineering engagements. The ideal candidate will have a strong hands-on background in data engineering with specific expertise in Spark, PySpark, and Python. Additionally, experience with cloud-native data engineering platforms like Databricks, Azure Data Engineering or Amazon Web Services (AWS) is highly desirable.
- Proven track record of designing and building scalable data pipelines and architectures.
- Hands-on experience with data processing and transformation.
- Strong understanding of data warehousing concepts and ETL processes.
- Excellent problem-solving skills and the ability to troubleshoot complex technical issues.
- Strong leadership and team management skills.
- Effective communication skills, both written and verbal.
- Familiarity with cloud services related to data storage, processing, and analytics (e.g., BigQuery, Redshift, S3, EMR).
- Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes).
- Familiarity with machine learning and data science concepts.
- Strong experience with data engineering technologies, particularly Spark, PySpark, and Python.
- Proven experience in data engineering or related roles.
- Industry certifications related to data engineering or cloud platforms are a plus.
- PySparkOptional Skills
- Travel Requirements
- Not SpecifiedAvailable for Work Visa Sponsorship?
- NoGovernment Clearance Required?
- NoJob Posting End Date
- August 26, 2026
Education
- B.Tech / M.Tech / MCA/MBA
- Degrees/Field of Study required:
- Bachelor of EngineeringDegrees/Field of Study preferred:Certifications (if blank, certifications not specified)
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Job application FAQ
Last updated 26 September 2026
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