1 day ago
Pune, India +2 moreStaff+
Responsibilities
- Design and implement AWS-based data engineering solutions aligned with enterprise standards.
- Build and optimize batch and streaming data pipelines using AWS-native and open-source tools.
- Develop SQL-driven transformations and Python-based data pipelines for analytics use cases.
- Design efficient data models for performance, scalability, and cost effectiveness.
- Own data engineering deliverables from development through production support.
- Perform performance tuning, cost optimization, capacity planning, and root-cause analysis for complex data pipeline issues.
- Ensure solutions meet security, reliability, scalability, AWS, and compliance requirements.
- Collaborate with architects, product owners, client stakeholders, DevOps, QA, and business stakeholders.
- Translate business and analytics requirements into AWS data engineering solutions and provide technical estimates and trade-offs.
- Participate in technical design reviews, code reviews, documentation, coding standards, and continuous improvement initiatives.
Requirements
- Six to ten years of total experience in data engineering and technical delivery.
- Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
- Strong hands-on experience with AWS data services including Amazon S3, AWS Glue, Athena, and Redshift.
- Experience designing cloud-native data lakes and data warehouse architectures on AWS.
- Strong SQL expertise for transformations, aggregations, analytics, and performance tuning.
- Strong Python programming skills for data engineering use cases.
- Hands-on experience with Spark or PySpark and distributed processing of structured, semi-structured, and unstructured data.
- Experience with schema design, partitioning, query optimization, data modeling, and scalable data ingestion and transformation workflows.
- Experience with Infrastructure as Code using Terraform and/or CloudFormation.
- Experience building and maintaining CI/CD pipelines for data platforms and exposure to containerized workloads.
- Strong communication, collaboration, ownership, and production stability skills.
- AWS Data Analytics or Solutions Architect certification is beneficial.
- Databricks, Snowflake, or other cloud data platform certifications are a plus.
- Experience with Kinesis, Kafka, MSK, lakehouse architectures, BI and analytics tools, data governance, data quality, metadata management, FinOps, CDP or MarTech data, and Agile delivery is beneficial.
Benefits
- Full-time permanent employment.
- Location: DGS India, Pune, Indiqube Orchid; brand: Merkle.
- Shift timing is 12 PM to 9 PM and/or 2 PM to 11 PM in the IST time zone.
Tech Stack
Categories
Data Engineering
About Dentsu
Dentsu is a global advertising and marketing services group that plans and buys media, develops creative campaigns, and builds data- and technology-led customer experiences for brands. It earns revenue from agency fees and media services across a network that includes Carat, iProspect, and Merkle. Founded in 1901 and headquartered in Tokyo, Dentsu is publicly traded in Japan and serves clients across many sectors worldwide.