Sr Data Engineer-AWS

Job Title: Senior Data Engineer

Location: Remote

Experience: 5–8 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. You’ll 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

• Design and develop reliable, reusable ETL/ELT pipelines using AWS Glue, Python, and Spark.
  
• 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

• Implement AWS-native data lake/lakehouse architectures using S3, Redshift, Glue Catalog, and Lake 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

• Ensure secure data architecture practices across AWS components using encryption, access control, and policy enforcement.
  
• 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

• Automate deployment of data infrastructure using CI/CD pipelines (GitHub Actions, Jenkins, or AWS CodePipeline).
  
• Create Docker-based containers and manage workloads using ECS or EKS.
  
• Monitor pipeline health, failures, and performance using CloudWatch and custom logs.
  

Collaboration & Communication

• Partner with the Data Platform Lead and AI Lead to align engineering efforts with AI product goals.
  
• 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

• Bachelor’s degree in Computer Science, Engineering, or equivalent.
  
• 5–8 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.
  

• Proficiency in Databricks, Unity Catalog, and Spark-based distributed data processing.
  
• 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.
  

Ready to build data solutions that fuel AI innovation?

Join Aptus Data Labs and play a key role in transforming raw data into enterprise intelligence.