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Data - Senior Engineer

Data - Senior Engineer

Iris Software

8 - 13 years

7 - 11 Lacs

noida

Posted:1 hour ago| Platform:

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Skills Required

python machine learning artificial intelligence aws ml continuous integration microsoft azure ci/cd aiml cloud platforms azure data factory data bricks configuration management data science data modeling spark gcp devops big data agile methodology

Work Mode

Work from Office

Job Type

Full Time

Job Description

The Principal Data Engineer will be a senior individual contributor responsible for designing, building, and optimizing advanced data solutions that power enterprise-wide analytics, AI/ML, and data-driven decision-making. Reporting directly to the Senior Director of Data Platforms, this role will serve as a technical expert and thought partner in scaling modern data architectures, enabling AI orchestration, and delivering robust, secure, and compliant data products.

This position is highly hands-on, requiring expertise in data engineering, Databricks, Python, AI/ML platforms, and orchestration frameworks. The Principal Engineer will work across functional teams to design and implement high-performance pipelines, ensure platform reliability, and set technical standards for the organizations data engineering practices.

Job Duties & Responsibilities

Design & Build Data Systems: Architect and implement scalable data pipelines, lakehouse/lake/warehouse environments, APIs, and orchestration workflows to support analytics, AI/ML, and business intelligence.
Enable AI & ML at Scale: Partner with Data Science and AI teams to productionize ML models, automate workflows, and enable AI orchestration frameworks (e.g., MLflow, Airflow, Databricks workflows).
Technical Leadership: Act as a hands-on subject matter expert in Databricks, Python, Spark, and related technologiesdriving adoption of best practices and mentoring other engineers.
Optimize Performance: Ensure data pipelines and platforms are highly available, observable, and performant at scale through monitoring, automation, and continuous improvement.
Ensure Compliance & Security: Build solutions that adhere to data governance, privacy, and regulatory frameworks (HIPAA, SOC 2, GCP, GDPR) within clinical research, life sciences, and healthcare contexts.
Collaborate Across Functions: Work closely with platform engineering, analytics, product management, and compliance teams to deliver aligned solutions that meet enterprise needs.
Advance Modern Architectures: Contribute to evolving data platform strategies, including event-driven architectures, data mesh concepts, and lakehouse adoption.

Location

This role is open to candidates working in the United States (remote or hybrid).

Basic Qualifications

Bachelors degree in Computer Science, Engineering, Data Science, or equivalent practical experience.
8+ years of data engineering experience in designing, implementing, and optimizing large-scale data systems.
Strong proficiency in Python, with production-level experience in building reusable, scalable data pipelines.
Hands-on expertise with Databricks (Delta Lake, Spark, MLflow), and modern orchestration frameworks (Airflow, Prefect, Dagster, etc.).
Proven track record of deploying and supporting AI/ML pipelines in production environments.
Experience with cloud platforms (AWS, Azure, or GCP) for building secure and scalable data solutions.
Familiarity with regulatory compliance and data governance standards in healthcare or life sciences.

Preferred Qualifications

Experience with event-driven systems (Kafka, Kinesis) and real-time data architectures.
Strong background in data modeling, lakehouse/lake/warehouse design, and query optimization.
Exposure to AI orchestration platforms and generative AI use cases.
Contributions to open-source projects or published work in data engineering/ML.
Agile development experience, including CI/CD, automated testing, and DevOps practices.

Mandatory Competencies

Development Tools and Management - Development Tools and Management - CI/CD

Tech - Agile Methodology

Data Science and Machine Learning - Data Science and Machine Learning - Gen AI

Data Science and Machine Learning - Data Science and Machine Learning - AI/ML

Big Data - Big Data - SPARK

DevOps/Configuration Mgmt - Cloud Platforms - AWS

DevOps/Configuration Mgmt - Cloud Platforms - GCP

Cloud - Azure - Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage, Event Hubs, HDInsight

Beh - Communication and collaboration

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Data - Senior Engineer