Data Engineer

Clinisys; Bengaluru; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Clinisys in Bengaluru, India, is seeking a Data Engineer to build reliable, scalable data platforms, pipelines and products that power analytics, reporting and AI initiatives.

You will collaborate with domain owners and platform teams to ingest, transform, and serve high-quality data with strong governance, observability and cost efficiency, enabling faster, better decisions and AI-driven insights across the organization. This role offers growth and the chance to shape data foundations.

Qualifications

• Bachelor’s degree in CS, Data Engineering, IS, or related field.
• 5+ years of production data pipelines and data models.
• Strong SQL and at least one data engineering language (Python).
• Experience with Spark, dbt, Airflow-like orchestration and cloud platforms (Snowflake, Databricks, MS Fabric).
• Knowledge of data modeling (dimensional, normalized, data products) and data quality.
• Familiarity with APIs, file ingestion, and event/stream processing.
• Strong troubleshooting and cross-team collaboration.

Responsibilities

• Evaluate cloud architecture for a unified data platform.
• Partner with BI teams to deliver analytics-ready datasets.
• Design and build scalable ETL/ELT pipelines.
• Ensure data quality with automated checks and lineage.
• Optimize storage, performance, and costs.
• Create reusable data ingestion and validation frameworks.
• Enforce data security and governance controls.
• Document pipelines and data products for support.

Skills

SQL

Python

Spark

dbt

Airflow

Snowflake

Databricks

MS Fabric

Data Modeling

Data Quality

APIs

ETL/ELT

Education

Bachelor’s degree

Tools

Airflow

dbt

Snowflake

Databricks

MS Fabric

Job description

Purpose

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.

Purpose

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.

Clinisys’ AI Philosophy

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.

Essential Functions

• 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.

Required Experience And Education

• 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.

Physical Requirements

• 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