Data Engineer
Yesterday Bengaluru, India
About us
Cargill provides food, ingredients, agricultural solutions and industrial products to nourish the world in a safe, responsible and sustainable way.
- Size: 10,000+ employees
- Industry: Natural Resources: Agriculture and Food Processing
Why you should apply for a job to Cargill:
4.1/5 in overall job satisfaction
4.5/5 in supportive management
71% say women are treated fairly and equally to men
71% would recommend this company to other women
79% say the CEO supports gender diversity
Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›
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
Qualifications
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
Additional Information
- Job category: Data Science
- Posted: yesterday