184. Data Engineer

sourcemeridian; Medellín; Sur place; COP 129 475 000 - 226 581 000; Plein temps

Avantages offerts par ce poste

Health and well-being benefits

Résumé du poste

Source Meridian in Colombia is seeking a Data Engineer to design and operate an AWS-native data platform for healthcare claims data. You will build Spark-based pipelines on S3, implement tokenization workflows, and ensure data integrity while interfacing with US stakeholders.

This role emphasizes privacy, security, and cost optimization, with orchestration via Airflow and dbt collaboration. You will work with a team to deliver reliable ETL/ELT processes and scalable data models in a fast-paced

Qualifications

• 2+ years of professional experience in Data Engineering.
• Strong experience with Apache Spark (PySpark or Scala) including joins and performance tuning.
• Excellent SQL skills and solid data modeling fundamentals.
• Advanced English level to lead technical discussions with US stakeholders.
• Hands-on experience with the AWS data stack: S3, Athena, Glue Catalog, Lake Formation, Airflow.

Responsabilités

• Build and maintain Spark pipelines to process large-scale Parquet datasets on S3.
• Implement tokenization workflows and dataset intersection logic.
• Process healthcare claims data with accurate identity mapping and data integrity.
• Orchestrate data pipelines using Airflow and AWS-native tooling.
• Develop reliable ETL/ELT processes with monitoring and reprocessing.
• Optimize performance and cost across Spark, S3, and Athena.
• Contribute to dbt models when applicable.
• Collaborate with cross-functional stakeholders with emphasis on privacy.

Connaissances

Data engineering

Apache Spark

SQL proficiency

English proficiency

Outils

AWS data stack

S3

Athena

Glue Catalog

Airflow

dbt

Description du poste

We're looking for a Data Engineer to join Source Meridian.

About Source Meridian

Source Meridian is a development software company that works to solve the industry's most challenging problems in healthcare practices. We are laser focused on specific technologies in the healthcare and life science industries: Healthcare technology, artificial intelligence, and healthcare interoperability.

About the Role

We're looking for a Data Engineer to help build and operate an AWS-native data platform processing healthcare claims data and tokenized identifiers. You'll design and implement Spark-based pipelines that transform, intersect, and enrich tokenized datasets stored primarily as Parquet on S3, queried via Athena and related AWS services. This environment intentionally avoids managed lakehouse platforms (e.g., no Databricks and no Snowflake)-you'll be doing "real" data engineering directly on AWS.

What You'll Do

• Build and maintain Spark pipelines to process large-scale Parquet datasets on S3.
• Implement tokenization workflows, including transit token → real token conversion and dataset intersection/join logic.
• Process and deliver healthcare claims datasets for matched individuals, ensuring accurate identity mapping and data integrity.
• Orchestrate data pipelines using Airflow and/or AWS-native orchestration tools when appropriate.
• Develop reliable, testable, and observable ETL/ELT processes (retries, idempotency, monitoring, reprocessing).
• Optimize performance and cost across Spark jobs, S3 partitioning/layout, and Athena query patterns.
• Contribute to dbt models when applicable (transformations, documentation, data quality checks).
• Collaborate with cross-functional stakeholders in a healthcare environment, with a strong focus on privacy and secure data handling.

Required Qualifications

• 2+ years of professional experience in Data Engineering.
• Strong experience with Apache Spark (PySpark or Scala), including joins, intersections, partitioning, and performance tuning.
• Excellent SQL skills and solid data modeling fundamentals.
• Advanced English level: able to lead technical discussions, write clear documentation, and work directly with US-based stakeholders.

Strong hands-on experience with the AWS data stack , including:

• Amazon S3 (Parquet datasets, partition strategies, data layout best practices)
• Amazon Athena (SQL, query optimization, managing large datasets)
• Familiarity with AWS-native data lake patterns (Glue Catalog, Lake Formation concepts are a plus)
• Experience building and operating pipelines using Airflow (DAGs, scheduling, dependencies, backfills).

Nice to Have

• Experience with dbt (core, tests, documentation, exposures).
• Familiarity with healthcare data (claims data, eligibility, member-level datasets).
• Experience with tokenization, identity resolution, or privacy-preserving data workflows.
• Knowledge of AWS security concepts such as IAM, KMS, encryption, and secure data handling .
• Experience running Spark on AWS (e.g., EMR) or Spark-on-containers architectures.

Tech Stack

• AWS-native architecture
• Amazon S3 + Parquet (core storage layer)
• Amazon Athena (query engine)
• Apache Spark (no Databricks)
• Airflow (orchestration)
• dbt (optional, as applicable)

Soft Skills

• Strong and empathetic leadership.
• Proven client-facing experience .
• Excellent communication skills .
• Strong expectation management abilities.
• Strategic mindset with a solution-oriented approach and strong decision-making skills.

What We Offer

• Permanent contract
• Learning and continuous growth environment
• Benefits package focused on health and well-being
• Competitive salary based on experience

Apply only if you reside in Colombia or Ecuador

At Source Meridian , you'll be part of a high-impact tech-health company, building products that truly make a difference.