Consultant - Databricks AWS
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Location
In office (Bengaluru)
Experience
5+ years exp
First seen by Alion on Nov 12, 2026. KPMG scores B on the Alion truth index.
Overview
Company
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Profile match
KPMG is a global professional services network headquartered in Amstelveen, Netherlands, and formed in 1987 through the merger of Peat Marwick International and Klynveld Main Goerdeler. The network provides audit and assurance, tax, and advisory services including deal advisory, risk consulting, and technology implementation. It is one of the Big Four accounting organisations, operating as a cooperative of legally separate member firms in more than 140 countries.
Backed by Dozen
Mandatory Skills:
- Bachelor's degree in computer science, data science, engineering, mathematics, information systems, or a related technical discipline
- 5+ years of relevant experience in data engineering roles
- Detailed knowledge of data warehouse technical architectures, data modelling, infrastructure components, ETL/ELT and reporting/analytic tools and environments, data structures, and hands-on SQL coding
- Proficient in programming languages: Python
- Experienced with Databricks designing, developing, and maintaining data pipelines and solutions using Databricks, Apache Spark, and other related tools (Unity Catalog, Workflow, Autoloader, Delta Sharing) to process large datasets and extract actionable business insights
- Experienced with AWS services such as Redshift, S3, EC2, Lambda, Athena, EMR, AWS Glue, Data Pipeline
- Experience building metrics decks and dashboards for KPIs, including the underlying data models
- Understand how to design, implement, and maintain a platform providing secured access to large datasets
Responsibilities:
- Master's degree in computer science, data science, engineering, mathematics, information systems, or a related technical discipline
- 5+ years of work experience with ETL, data modelling, and data architecture
- Experienced with Databricks designing, developing, and maintaining data pipelines and solutions using Databricks, Apache Spark, and other related tools (Unity Catalog, Workflow, Autoloader, Delta Sharing) to process large datasets and extract actionable business insights
- Experience or familiarity with newer analytics tools such as AWS Lake Formation, SageMaker, DynamoDB, Lambda, Elasticsearch
- Experience with data streaming services, e.g. Kinesis, Kafka
- Ability to develop experimental and analytic plans for data modeling processes, use strong baselines, and accurately determine cause-and-effect relations
- Proven track record partnering with business owners to understand requirements and developing analysis to solve their business problems
- Proven analytical and quantitative ability and a passion for enabling customers to use data and metrics to back up assumptions, develop business cases, and complete root cause analysis
Skills
AWS, Data Engineering, Databricks
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