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Expert Data & AI Engineer

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Onsite

Expert Data & AI Engineer

DSM Firmenich

Expert Data & AI Engineer

Skills

SQL QueriesPythonDatabricksAIAWSdbtPySparkAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Hyderabad, Telangana, India

Work mode:

Onsite

Published on:

7 September 2026

What they need


Job Summary

Job Title-Expert Data AI Engineer

Location - Hyderabad

At dsm-firmenich we strive to achieve a world where you dont have to choose between taste, texture, or health - and can enjoy it all. Our innovative ingredients, expertise, and solutions bridge the gap between the delicious, the nutritious, and the sustainable.

In this role you will design, maintain robust data pipeline and manage team, projects/initiatives ensuring seamless data integration and transformation. Collaborate with data modelers and business partners to drive impactful projects centered around our data.

Being a force for good is not optional. Diversity, Equity Inclusion is a shared responsibility woven into our daily work, benefiting our People, Customers Communities and driving business value. Equal access to opportunities is a given, belonging is a shared feeling, authenticity is celebrated.

Your Key Resposibilities

  • Provide technical recommendations and evaluate project feasibility and workloads.
  • Design and implement efficient pipeline architectures for data ingestion, transformation, and storage.
  • Develop modular, efficient code for data transformation and integration, ensuring adherence to modern development practices.
  • Perform data ingestion from source systems, including ETL processes, when tables are not available on the data platform.
  • Conduct regular pipeline maintenance and upgrades, troubleshooting and resolving issues to ensure optimal performance.
  • Implement data quality testing (automatic) and validation to maintain high standards of data integrity and reliability. Collaborate closely with other data engineers, data modelers, data stewards, BI developers, data scientists, and subject matter experts to ensure seamless data integration, knowledge sharing, and delivery of impactful solutions.

We Bring

  • Unique career paths across health, nutrition and beauty, explore what drives you and get the support to make it happen
  • A chance to impact millions of consumers every day, sustainability embedded in all we do
  • A science led company, cutting edge research and creativity everywhere, from biotech breakthroughs to sustainability game-changers, youll work on whats next.
  • Growth that keeps up with you, you join an industry leader that will develop your expertise and leadership
  • A culture that lifts you up. with collaborative teams, shared wins, and people who cheer each other on.
  • A community where your voice matters. it is essential to serve our customers well.

You Bring

  • Expert knowledge in dbt, SQL, Python, Spark (PySpark), Git, Azure DevOps and Databricks.

  • Expertise in cloud engineering (e.g., AWS, Azure); experience with infrastructureascode is a plus, and deploying CI/CD pipelines is a must.

  • Strong problemsolving skills.Experience handling scientific datasets for cheminformatics or bioinformatics (e.g., microbiome) is a plus.

  • 5 years of experience in creating and maintaining data pipelines.

  • Ability to collaborate closely with data experts and SMEs to ensure seamless data integration and transformation. Consistent application of best practices in coding, testing and documentation, delivering scalable and reliable data solutions with automated quality checks and monitoring tools.

  • Curiosity and a growth mindset, always asking

    Is there a better way

    to leverage data for smarter decisionmaking.

  • Strong focus on deployment development and automation, bringing handson experience in designing, building and optimizing automated deployment pipelines across environments.

  • While the role is technically oriented, leadership in team management, project oversight, and stakeholder engagement is a critical part of the position

  • Experience with FAIR data principles, data governance, and data standards commonly used in scientific domains.

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