Data Engineer

Cargill • Meat & Poultry • Animal Nutrition • Bachelor's Degree • Python • Java • SQL • Scala • ETL/ELT • Data Vault • 7 days ago
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Salary
≈ $16k – $39k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Middle · 4+ years exp

Confirmed on the employer's own hiring board on Oct 21, 2026. First seen by Alion on Oct 15, 2026. Cargill scores A on the Alion truth index.

Overview
Company
Impact
Profile match

Cargill

Cargill is a global food, agriculture, and industrial products enterprise. The company provides agricultural commodity trading and processing, food ingredients, bio-industrial materials, animal nutrition, supply chain logistics, and financial risk management services to food manufacturers, farmers, and commercial clients. Headquartered in Wayzata, Minnesota, United States, the organization serves clients and partners across more than 70 countries worldwide.
cargill.com • HQ: Wayzata, United States • Meat & Poultry • Animal Nutrition • Food Ingredients • 5000+ employees • Est. 1865
Tech stack of Cargill
Backed by Silicon Valley Investclub

Job Purpose and Impact

We are seeking a skilled Data Engineer to design, develop, and maintain scalable data pipelines and platforms that enable reliable data ingestion, transformation, storage, and analytics. The ideal candidate will have strong expertise in cloud-based data engineering, ETL/ELT frameworks, data warehousing, and modern big data technologies

Key Accountabilities

  • Design and develop scalable data ingestion and processing pipelines.
  • Build and maintain batch and real-time data integration solutions.
  • Develop ETL/ELT workflows to transform and load data from various source systems.
  • Design and optimize data models for analytics and reporting.
  • Ensure data quality, integrity, governance, and security standards are maintained.
  • Monitor, troubleshoot, and optimize data pipelines and workloads.
  • Collaborate with product owners, business stakeholders, architects, and data scientists to deliver data solutions.
  • Implement data observability, monitoring, and alerting mechanisms.
  • Support cloud migration and modernization initiatives.
  • Create and maintain technical documentation, data lineage, and operational runbooks.

Qualifications

    • Have a Bachelor's degree with minimum 4 years of professional experience.
    • Experience with Snowflake, Databricks, Redshift, BigQuery, or Synapse.
    • Knowledge of Apache Kafka or other streaming technologies.
    • Experience with dbt and modern data stack tools.
    • Familiarity with DataOps and MLOps practices.
    • Understanding of data governance, metadata management, and data quality frameworks.
    • Cloud certifications (AWS, Azure, or GCP) are preferred

  • Technical Skills

    • Programming: Python, SQL, Scala, Java
    • Data Processing: Spark, Hive, Airflow
    • Cloud: AWS (S3, Glue, Lambda, EMR), Azure, GCP
    • Databases: SQL Server, Oracle, PostgreSQL, Snowflake
    • Streaming: Kafka, Kinesis
    • DevOps: Git, Jenkins, CI/CD
    • Data Modeling: Star Schema, Snowflake Schema, Data Vault
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