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Senior Consultant – Tech Consulting, AI and Data
EYData Engineer at EY responsible for building and maintaining ETL processes and managing databases. Working with emerging technologies to support analytics and business intelligence initiatives.
Tech Stack
Tools & technologiesAmazon RedshiftApacheAWSAzureBigQueryCassandraCloudETLHadoopKafkaMongoDBMySQLNoSQLPostgresPythonScalaSparkSQL
About the role
Key responsibilities & impact- Design, develop and maintain scalable ETL (Extract, Transform, Load) processes to efficiently extract data from various structured and unstructured sources, ensuring accuracy, consistency and performance optimization.
- Architect and manage database systems to support large-scale data storage and retrieval, ensuring high availability, security and efficiency in handling complex datasets.
- Integrate and transform data from multiple sources including APIs, on-premises databases and cloud storage, creating unified datasets to support data-driven decision-making across the organization.
- Collaborate with business intelligence analysts, data scientists and other stakeholders to understand specific data needs, ensuring the delivery of high-quality, business-relevant datasets.
- Monitor, troubleshoot and optimize data pipelines and workflows to resolve performance bottlenecks, improve processing efficiency and ensure data integrity.
- Develop automation frameworks for data ingestion, transformation and reporting to streamline data operations and reduce manual effort.
- Work with cloud-based data platforms and technologies such as AWS (Redshift, Glue, S3), Google Cloud (Big Query, Dataflow), or Azure (Synapse, Data Factory) to build scalable data solutions.
- Optimize data storage, indexing, and query performance to support real-time analytics and reporting, ensuring cost-effective and high-performing data solutions.
- Lead or contribute to special projects involving data architecture improvements, migration to modern data platforms, or advanced analytics initiatives.
Requirements
What you’ll need- Minimum 5 years of relevant work experience, with at least 2 years in designing and maintaining data pipelines, ETL processes and database architectures.
- Bachelor’s degree (B.E./B.Tech) in Computer Science or IT, or Bachelor’s in Data Science, Statistics, or related field.
- Strong expertise in SQL, Python, or Scala for data processing, automation and transformation.
- Hands-on experience with big data frameworks such as Apache Spark, Hadoop, or Kafka for real-time and batch processing.
- Experience in cloud data platforms including AWS Redshift, Google Big Query, or Azure Synapse, with proficiency in cloud-native ETL and data pipeline tools.
- Strong understanding of data modeling principles, relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, Cassandra).
Benefits
Comp & perks- Support, coaching and feedback from some of the most engaging colleagues around
- Opportunities to develop new skills and progress your career
- The freedom and flexibility to handle your role in a way that’s right for you
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
ETLSQLPythonScalaApache SparkHadoopKafkadata modelingrelational databasesNoSQL databases
Soft Skills
collaborationtroubleshootingoptimizationcommunicationleadership
Certifications
Bachelor’s degree in Computer ScienceBachelor’s degree in Data ScienceBachelor’s degree in Statistics