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.
Preferred Additional Skills
- 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.