Data Engineer

Source Meridian; Medellín; Presencial; COP 60.000.000 - 120.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Permanent contract

Learning and growth environment

Health and wellbeing benefits

Descripción de la vacante

Source Meridian is seeking a Data Engineer to build and operate an AWS-native data platform handling healthcare claims data. You will design Spark pipelines and work with Parquet on S3, queries via Athena, and orchestrate with Airflow.

Join a privacy-conscious healthcare-focused team and contribute to dbt models when applicable. Ideal candidates have 2+ years in data engineering, strong Spark and AWS data stack experience, solid SQL, and excellent English to collaborate with US-based

Formación

• 2+ years of professional experience in Data Engineering.
• Strong experience with Apache Spark (PySpark/Scala), including joins, intersections, partitioning, and performance tuning.
• Strong hands-on experience with the AWS data stack, including S3 (Parquet datasets), Athena, Glue catalog, Lake Formation concepts.
• Experience building and operating pipelines using Airflow.
• Excellent SQL skills and solid data modeling fundamentals.
• Advanced English level for leading technical discussions with US-based stakeholders.

Responsabilidades

• Build and maintain Spark pipelines to process large-scale Parquet datasets on S3.
• 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.

Conocimientos

Spark

AWS

Airflow

SQL

English

Herramientas

dbt

S3

Athena

Glue

Descripción del empleo

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.

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 withApache Spark(PySpark or Scala), including joins, intersections, partitioning, and performance tuning.

Strong hands-on experience with theAWS 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 usingAirflow(DAGs, scheduling, dependencies, backfills).

ExcellentSQLskills and solid data modeling fundamentals.

Advanced English level: able to lead technical discussions, write clear documentation, and work directly with US-based stakeholders.

Nice to Have

Experience withdbt(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 asIAM, KMS, encryption, and secure data handling.

Experience running Spark on AWS (e.g., EMR) or Spark-on-containers architectures.

Amazon S3 + Parquet (core storage layer)

Amazon Athena (query engine)

Airflow (orchestration)

dbt (optional, as applicable)

Soft Skills

Strong and empathetic leadership.

Provenclient-facing experience.

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

We’d love to meet you