Senior Data Engineer (AWS)

Roles and Responsibilities

• Create and maintain optimal data pipeline architecture for ETL/ELT into structured data
• Assemble large, complex data sets that meet business requirements and create multi-dimensional modelling like Star Schema and Snowflake Schema
• Expert level experience in creating scalable data warehouse including Fact tables, Dimensional tables and ingest datasets into cloud-based tools.
• Identify, design, and implement internal process improvements including automating manual processes and optimizing data delivery
• Collaborate with stakeholders to ensure seamless integration of data with internal data marts, enhancing advanced reporting.
• Setup and maintain data ingestion, streaming, scheduling, and job monitoring automation using AWS services including Lambda, Code Pipeline, Glue, S3, and Redshift.
• Build analytics tools that utilize the data pipeline to provide actionable insight into customer acquisition and operational efficiency.
• Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs.
• Utilize GitHub for version control, code collaboration, and repository management
• Create data tools for analytics and data scientist team members
• Ensure data privacy and compliance with relevant regulations when handling customer data.
• Maintain data quality and consistency within the application

Requirements

1Strong Senior Data Engineer Profile with AWS data-warehousing and pipeline expertise

2Mandatory (Experience): Must have at least 4+ years of hands-on data engineering experience with the recent 2+ years in AWS cloud data warehouses and AWS cloud services

3Mandatory (Tech skill 1): Must have advanced SQL knowledge and hands-on experience with relational databases and query authoring, plus a cloud data warehouse like AWS Redshift.

4Mandatory (Tech skill 2): Must have expert-level experience creating scalable data warehouses — Fact tables, Dimensional tables, and ingesting datasets into cloud-based tools.

5Mandatory (Tech skill 3): Must have strong multi-dimensional data modelling experience — Star Schema, Snowflake Schema, normalization/de-normalisation, joins, OLAP cube modelling, and schema evolution while maintaining data integrity.

6Mandatory (Tech skill 4): Must have hands-on experience creating and maintaining optimal ETL/ELT data pipeline architecture into structured data.

7Mandatory (Tech skill 5): Must have experience setting up and maintaining data ingestion, streaming, scheduling, and job-monitoring automation using AWS services — Lambda, Glue, S3, Redshift, and Code Pipeline (CI/CD)

8Mandatory (Tech skill 6): Must have experience building and optimizing big-data pipelines, architectures, and datasets, including data compression into PARQUET and SQL performance tuning.

9Mandatory (Tech skill 7): Must have experience with GitHub for version control, code collaboration, code reviews, branching strategies, and continuous integration.

10Mandatory (Tech skill 8): Must have strong analytical skills across structured and unstructured datasets, with experience performing root-cause analysis to answer business questions and identify improvements.

11Mandatory (Tech skill 9): Must have experience collaborating with cross-functional teams and Global IT to gather requirements and align work with business objectives, and ensuring data privacy/compliance (e.g. GDPR).

12Mandatory (Tech skill 10): Working knowledge of message queuing, stream processing, and highly scalable big-data stores; familiarity with Agile working models.

13Mandatory (Project Alignment): Current or recent role must clearly demonstrate hands-on work with AWS data platforms and ETL pipeline implementation—resume must describe specific projects, tools used, and candidate's direct scope

14Mandatory (Education): Bachelor's or master's degree in Technology and Computer Science background

15Mandatory (Availability): Must be an immediate joiner or currently serving notice period, able to start within the next week

16Mandatory (Note 1) : Role is Hybrid, WFH flexibility as well up to 6 days a month

17Mandatory (Note 2): CTC is inclusive of 20% variable

18Preferred (Domain): Healthcare/Pharmaceutical/Life Sciences industry experience