Senior Data Engineer (Healthcare Data)

Bosnia and Herzegovina·Tuzla/sarajevosenior

Data EngineerData

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Quick Summary

Overview

Salt Square is a growing outsourcing company providing high-quality software development services to clients across a wide range of industries.

Technical Tools

Data EngineerData

Salt Square is a growing outsourcing company providing high-quality software development services to clients across a wide range of industries. Our team is composed of skilled and dedicated professionals delivering innovative solutions that meet and exceed client expectations.

Our mission is to build reliable, scalable, and future-ready digital solutions tailored to each client’s unique business needs. We foster a team-first culture where collaboration, continuous learning, and technical excellence are core values. From supporting startups in launching their first products to helping global enterprises scale their operations, we strive to deliver outstanding value on every project.

As a Data Engineer at Salt Square, you will build and maintain scalable healthcare data pipelines, transform legacy claims and clinical data into the FHIR® (Fast Healthcare Interoperability Resources) standard, and support population health analytics and regulatory compliance for payers and providers.

We are looking for an experienced Senior Data Engineer to design, implement, and optimize scalable data solutions. You will work with modern data technologies, distributed systems, and cloud platforms to build efficient, high-performance data pipelines that support analytics, AI/ML, and business intelligence initiatives.

Responsibilities

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Design, develop, and implement robust ETL/ELT pipelines for large-scale data ingestion, transformation, and storage.
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Ensure data quality, integrity, and governance through validation techniques, data monitoring, and automated testing.
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Work with data scientists, analysts, platform engineers, and business stakeholders to develop scalable, reusable data solutions.
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Automate deployments and testing using CI/CD pipelines with Git, Terraform, GitHub Actions, or Jenkins.
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Design and build custom data tools and abstractions for analytics, machine learning, and real-time data processing.
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Partner with DevOps and platform teams to set up efficient deployment and monitoring processes for internal and external data products.
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Develop alerting, monitoring, and observability frameworks that keep pipelines reliable and catch issues early.
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Contribute to data architecture and strategy, improving scalability, performance, and cost efficiency.
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Keep up with emerging technologies and best practices to continuously improve data engineering capabilities.

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5+ years of hands-on data engineering experience, with expertise in distributed data processing and big data frameworks such as Apache Spark, Apache Iceberg, Trino, Apache Airflow, dbt, or Dagster.
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Advanced Scala or Python skills for data transformation and automation.
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Experience with real-time streaming technologies such as Apache Flink, Spark Streaming, or Kafka.
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Strong experience in Spark performance tuning and optimizing large-scale data workflows.
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Proficiency in SQL and database management, including hands-on work with MPP databases such as Amazon Redshift, Snowflake, or Teradata.
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Familiarity with cloud data services (AWS, RDS, DynamoDB) and containerized infrastructure (EKS, Docker, Kubernetes).
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Hands-on experience applying DevOps and CI/CD practices to data engineering with GitHub Actions, Jenkins, or Terraform.
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A proven track record of building monitoring, alerting, and observability tools that keep pipelines highly available and reliable.
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Experience with data mapping, validation, and testing frameworks that ensure accuracy and consistency.
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Exposure to machine learning and deep learning with PyTorch, TensorFlow, or Keras (PyTorch preferred).
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Familiarity with ML workflows and MLOps tools for model deployment and lifecycle management.
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A self-starter mindset, strong problem-solving skills, and comfort in a fast-paced, agile environment.

Nice to Have

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Experience with healthcare data standards such as HL7 and FHIR, and with regulatory compliance.
Familiarity with reporting and visualization tools such as Superset, Grafana, or Tableau.
Understanding of data security, compliance, and governance frameworks such as HIPAA, GDPR, and SOC 2.