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Zifo

Senior Clinical Data Engineer

  • Seen live on Zifo's site today
  • Senior
Pay
Not stated
Location
Chennai, Tamil Nadu, India
Open for
9+ days
First seen
Oct 26, 2026
Apply on Zifo's site (opens in a new tab)

Posting record

No flags

Open 9+ days

The posting's record, oldest first
  1. Zifo's site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Zifo, so its true age is longer.

Last checked Nov 4, 2026.

How well do you match?

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What it asks of you

5+ years of experience
“5+ years of experience in Data Engineering, Software Engineering, or a related technology role.” (quoted from the posting)

What the posting discloses

Not stated: Pay, real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Some employers add pay only on their own site. Check the original posting before you rule it out.

Skills mentioned

About the role

We are looking for an experienced Senior Clinical Data Engineer to design, build, and manage scalable data pipelines supporting clinical trials.

In this role, you will be responsible for the end-to-end ingestion, integration, transformation, and delivery of clinical data from multiple source systems into enterprise data platforms such as data lakes and data warehouses. You will work closely with clinical data teams, analytics teams, and other downstream consumers to ensure that clinical data is reliable, traceable, high quality, and ready for use.

Requirements

  • Bachelor's degree ( BE/BTech/BS/BA ) in Computer Science, Information Technology, Engineering, Life Sciences, Health Sciences, or a related discipline.
  • 5+ years of experience in Data Engineering, Software Engineering, or a related technology role.
  • Strong hands-on programming experience with Python and SQL .
  • Hands-on experience with AWS cloud platform .
  • Experience designing and deploying production-grade ETL/ELT data pipelines in cloud environments.
  • Hands-on experience with distributed/big-data processing technologies such as Apache Spark .
  • Experience with workflow orchestration and scheduling using Apache Airflow .
  • Experience working with data lakes and/or cloud data warehouses , such as Snowflake or Amazon Redshift.
  • Strong understanding of database concepts, data modeling, data integration, and large-scale data processing.
  • Experience handling semi-structured data formats such as JSON and XML .
  • Experience building or consuming REST/API-based integrations .
  • Familiarity with source control and CI/CD tools such as GitLab/GitHub .
  • Strong understanding and practical application of the Software Development Life Cycle (SDLC) .

Clinical Domain Experience

  • Experience working with clinical trial data and clinical data workflows.
  • Familiarity with clinical systems and data sources such as EDC/eCRF, CTMS, and other clinical trial source systems .
  • Ability to understand study-level data requirements and translate them into scalable technical solutions.
  • Experience coordinating or supporting study-level data transfer and integration specifications is preferred.
  • Understanding of data quality, traceability, validation, and regulatory expectations within a clinical environment is highly desirable.

Key Competencies

  • Strong analytical and critical-thinking skills.
  • Excellent problem-solving and troubleshooting abilities.
  • Ability to independently own technical deliverables while working effectively within cross-functional teams.
  • Strong communication skills with the ability to collaborate with both technical and clinical stakeholders.
  • Ability to understand complex data requirements and translate them into practical engineering solutions.
  • Strong focus on data quality, reliability, scalability, and automation .
  • Ability to manage priorities and deliver within clinical study timelines.

Technology Landscape

Programming: Python (Advanced)

Big Data: Apache Spark

Orchestration: Apache Airflow

Cloud: AWS

Data Platforms: Amazon Redshift / Data Lakes

Databases: SQL

Data Integration: REST APIs, JSON, XML, file-based integrations

DevOps: GitLab / GitHub, CI/CD

Clinical Systems: EDC/eCRF, CTMS, clinical source systems

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