Aptus Data Labs - Senior Data Engineer - ETL/AWS Platform

Job Title : Senior Data Engineer

Location : Remote/Bangalore/WFH

Experience : 58 Years

Employment Type : Full-Time

About the Role :

Aptus Data Labs is looking for a talented and proactive Senior Data Engineer to help build the backbone of our enterprise data and AI initiatives. Youll work on modern data lake architectures and high-performance pipelines in AWS, enabling real-time insights and scalable analytics. This role reports to the Head Data Platform and AI Lead, offering a unique opportunity to be part of a cross-functional team shaping the future of data-driven innovation.

Key Responsibilities :

Data Engineering & Pipeline Development :

- Process structured and semi-structured data (e.g., JSON, Parquet, CSV) efficiently for analytics and AI

workloads.

- Build automation and orchestration workflows using Airflow or AWS Step Functions.

Data Lake Architecture & Integration :

Formation.

- Consolidate data from APIs, on-prem systems, and third-party sources into a centralized platform.

- Optimize data models and partitioning strategies for high-performance queries.

Security, IAM & Governance Support :

- Implement and manage AWS IAM roles and policies to control data access across services and users.

- Collaborate with platform and security teams to maintain compliance and audit readiness (e.g., HIPAA, GxP).

- Apply best practices in data security, privacy, and identity management in cloud environments.

DevOps & Observability :

- Create Docker-based containers and manage workloads using ECS or EKS.

- Monitor pipeline health, failures, and performance using CloudWatch and custom logs.

Collaboration & Communication :

- Engage with analysts, data scientists, and business teams to gather requirements and deliver data assets.

- Contribute to documentation, code reviews, and architectural discussions with clarity and confidence.

Required Qualifications :

- Bachelors degree in computer science, Engineering, or equivalent.

- 58 years of experience in data engineering, preferably in AWS cloud environments.

- Proficient in Python, SQL, and AWS services: Glue, Redshift, S3, IAM, Lake Formation.

- Experience managing IAM roles, security policies, and cloud-based data access controls.

- Hands-on experience with orchestration tools like Airflow or AWS Step Functions.

- Exposure to CI/CD practices and infrastructure automation.

- Strong interpersonal and communication skills able to convey technical ideas clearly.

Preferred Additional Skills :

- Background in Pharma, Life Sciences, or other regulated environments (GxP, HIPAA).

- Experience with EMR, Snowflake, or hybrid-cloud data platforms.

- Experience with BI/reporting tools such as Power BI or QuickSight.

- Knowledge of integration tools (Boomi, Kafka) or real-time streaming frameworks.