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 solid 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, Big Query, or Synapse. Knowledge of Apache Kafka or other streaming technologies. Experience with dbt and modern data stack tools. Familiarity with Data Ops 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, JavaData Processing: Spark, Hive, AirflowCloud: AWS (S3, Glue, Lambda, EMR), Azure, GCPDatabases: SQL Server, Oracle, PostgreSQL, SnowflakeStreaming: Kafka, KinesisDev Ops: Git, Jenkins, CI/CDData Modeling: Star Schema, Snowflake Schema, Data Vault

📌 Data Engineer. (India)
🏢 Cargill
📍 India