As a Data Engineer, you’ll build and operate reliable, scalable data platforms, data pipelines and data products that power analytics, reporting, and AI initiatives across Clinisys. You’ll partner with domain owners and platform teams to ingest, transform, and serve high-quality data with strong governance, observability, and cost efficiency. Your work will enable faster, better decisions and support AI-first outcomes through trusted data foundations.
Building an AI-first organization is central to Clinisys’ purpose and the impact we deliver. As a global provider of intelligent diagnostic informatics solutions, we build AI-enabled, cloud-based platforms to enhance diagnostic workflows across healthcare, life sciences, and public health. By applying intelligent technology thoughtfully and responsibly, we help laboratories and test environments operate more effectively, generate meaningful insights at scale, and ultimately support healthier and safer communities. Operating across more than 30 countries, Clinisys expects all colleagues—regardless of role or function—to work confidently with AI-enabled tools, apply digital and analytical thinking, and continuously adapt as technologies evolve. We must drive an AI-first sense of purpose and urgency.
· Evaluate Cloud Architecture: Provide technical leadership in evaluating, selecting, and implementing the company’s foundational unified cloud data platform.
· Support BI and Analytics: Partner closely with BI and business teams to deliver high-quality, analytics-ready datasets, custom schemas, and self-service data consumption models.
· Design and Build Pipelines: Construct and maintain scalable batch and streaming ETL/ELT pipelines to integrate enterprise applications, product systems, and external sources.
· Ensure Data Quality: Implement automated quality checks, reconciliation processes, and lineage documentation to guarantee accurate business metrics and rapid issue remediation.
· Optimize Workflow Operations: Establish strong pipeline testing, monitoring, alerting, and CI/CD practices to meet data freshness and reporting SLAs.
· Control Costs and Performance: Optimize data storage and compute efficiency through strategic partitioning, indexing, query tuning, and workload management.
· Create Reusable Frameworks: Build and maintain reusable code libraries for data ingestion, transformation, and validation to accelerate delivery of business insights.
· Enforce Security and Governance: Partner with Security and Compliance to implement data access controls, masking, encryption, retention policies, and robust auditability.
· Document and Share Knowledge: Maintain clear documentation for pipelines, data products, and operational runbooks to ensure team supportability and data definitions.
· Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent work experience.
· Proven experience (5+ years) building and operating production data pipelines and data models.
· Strong proficiency in SQL and at least one programming language commonly used for data engineering (e.g., Python).
· Experience with modern data processing and orchestration concepts (e.g., Spark, dbt, Airflow-like orchestration) and cloud data platforms (e.g., Snowflake, Databricks, MS Fabric, etc.).
· Knowledge of data modeling techniques (dimensional, normalized, and data product approaches) and data quality practices.
· Familiarity with APIs, file-based ingestion, and event/stream processing patterns.
· Strong troubleshooting skills and ability to work across teams to resolve data issues quickly and permanently.
· Work is performed in a typical office setting with minimal health or safety hazards exposure—prolonged periods of sitting at a desk and working on a computer.
· Up to 20% travel may be required.
· Moderate lifting/carrying 15-44 lbs; use of fingers, walking/standing 2-6 hours
· Exposure to hazardous materials or various weather conditions
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
*Clinisys acquired Orchard Software July 2025 (see press release https://tinyurl.com/clinisysnews)*
Clinisys delivers over 45 years of laboratory informatics expertise – built through the combined strength of trusted companies and specialists brought together under one global brand.
Today, we support more than 7,000 labs across 39 countries, helping them manage data, maximize throughput, and ensure quality across healthcare, contract services, public health, water quality, environmental sciences, toxicology, crop science, food & beverage, and life sciences industries. With our newest addition of proven solutions, we’ve also expanded our reach into physician office, reference, and veterinary laboratories, further strengthening our commitment to excellence and innovation.
In the future, we aim to expand into biotech and pharma to continue growing our mission of enabling healthier and safer communities.
Our solutions are designed to scale for the evolving needs of modern labs, and we’re committed to supporting every type of laboratory or remote testing environment – from public or private sector, in-house or outsourced. With headquarters in Tucson, AZ, and key offices in Raleigh, NC, Carmel, IN, Ghent BE, Woking UK, Bangalore IN, Kolkata IN, and across Europe, Clinisys is proud to be the global leader in lab informatics, holding ~24% of the global market share.
At our core is a people-first culture – driven by passionate experts who’ve spent decades helping labs run smarter and more efficiently.
Informatics is more than technology; it’s our path to a more connected, resilient, and thriving world.
𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿 𝗵𝗼𝘄 𝗖𝗹𝗶𝗻𝗶𝘀𝘆𝘀 𝗶𝘀 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗹𝗮𝗯 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝘀 – 𝗰𝗼𝗻𝗻𝗲𝗰𝘁 𝘄𝗶𝘁𝗵 𝘂𝘀 𝗮𝗻𝗱 𝗯𝗲 𝗽𝗮𝗿𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗴𝗹𝗼𝗯𝗮𝗹 𝗵𝗲𝗮𝗹𝘁𝗵.
