Spcialist , Data Engineering

Design, build, and operate batch and streaming data pipelines to ingest data from multiple sources into an AWS data lake / lakehouse and data warehouse .

Develop and maintain ETL/ELT transformations using Python , PySpark , and SQL; optimize jobs for performance, cost, and reliability.

Partner with Data Analysts, Data Scientists, and business stakeholders to understand use cases and deliver curated, analytics-ready datasets and features.

Implement data quality controls (validation rules, reconciliation, anomaly checks), define SLAs/SLOs , and contribute to metadata, lineage , and data catalog practices.

Use orchestration and observability to run pipelines reliably (e.g., Databricks Workflows , AWS Step Functions , scheduling, logging, monitoring, alerting).

Apply engineering best practices: unit/integration testing , automated data tests , code reviews, and quality gates within CI/CD .

Model and publish data for BI/analytics using dimensional modeling (star/snowflake), facts & dimensions, and slowly changing dimensions (SCD) .

Write and tune advanced SQL for profiling, transformations, and performance troubleshooting across large datasets.

Build on AWS using services such as S3 , Glue , Lambda , Step Functions , EMR , and CloudWatch; follow security best practices (IAM, encryption, least privilege).

Provision and manage cloud resources using Infrastructure as Code (e.g., Terraform ) across dev/test/prod environments.

Package and deploy workloads using Docker (and where applicable ECS/Fargate); manage dependencies and runtime configurations.

Use GitHub for version control (branching strategies, pull requests, code reviews) and set up CI/CD for automated build, test, and deployment.

Develop scalable processing on Databricks / Apache Spark using PySpark and lakehouse concepts (e.g., Delta Lake , ACID, schema evolution).

Use notebooks (e.g., Jupyter/Databricks) for exploration and PoCs, then productionize solutions with reusable modules, tests, and deployment pipelines.

Work in an Agile delivery model (planning, daily sync, reviews, retros), providing accurate estimates and proactively managing risks/dependencies.

Create and maintain technical documentation (data contracts, pipeline specs, runbooks) and support operational handoffs.

5+ years of hands-on experience in data engineering building production pipelines and data 5+ years of hands-on experience in data engineering building production pipelines and data platforms.

Strong AWS experience: S3 , Glue , Lambda , Step Functions , EMR (and/or ECS/Fargate), plus CloudWatch; solid grasp of IAM and encryption.

Nice to have: AWS certification (Developer/Architect) or equivalent demonstrated expertise.

Experience working in Agile teams; strong collaboration, communication, and stakeholder management skills.

Experience with Databricks and lakehouse capabilities (e.g., Delta Lake, job/workflow orchestration, cluster tuning) is strongly preferred.

Strong SQL skills including complex joins/window functions, data profiling, and performance tuning; understanding of dimensional modeling concepts.

Proficient in Python and PySpark with solid Spark fundamentals (partitioning, shuffle, caching, file formats) and ability to debug/optimize.

Strong with GitHub , CI/CD concepts, and engineering practices (code reviews, branching, release management); working knowledge of Docker and Terraform .

Demonstrated ability to work across teams, drive alignment, and take ownership to deliver outcomes (including production support/on call as needed).

Nice to have experience in ETL tools such as DBT, Matillion and data quality/testing frameworks (e.g., Collibra) and data governance tools such as Immuta

Nice to have experience with orchestration tools (e.g., Airflow), streaming (Kafka/Kinesis), and modern table formats (Delta/Iceberg/Hudi).

Bachelor’s degree in computer science, Engineering, or related field (or equivalent practical experience).

We are known as well-known org Inc., Rahway, New Jersey, USA in the United States and Canada and MSD everywhere else. For more than a century, bringing forward medicines and vaccines for many of the world's most challenging diseases. Today, our company continues to be at the forefront of research to deliver innovative health solutions and advance the prevention and treatment of diseases that threaten people and animals around the world.

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