Data Engineer

Company Description
Saatvik Agro is the agro-ingredient unit of the Saatvik Group, specializing in high-quality maize-based ingredients used in food, nutrition, animal feed, and industrial applications. The organization focuses on purity and scientific rigor, converting responsibly sourced maize into functional and reliable ingredient solutions. Its products are designed to meet the evolving needs of modern manufacturers who demand consistency, performance, and safety. Guided by the belief that better ingredients create better outcomes, Saatvik Agro aims to support customers in delivering superior products to their markets.
Role Description
We are looking for a Data Engineer for a full-time, on-site opportunity based in Morena, Madhya Pradesh, India.
The role is suitable for fresh graduates and early-career technology professionals interested in working across Data Engineering, SQL, Python, ETL/ELT, Data Pipelines, Databases, Cloud, Data Warehousing, Analytics, and Enterprise Data Systems.
The Data Engineer will work closely with IT, software, analytics, finance, production, supply chain, sales, operations, and other business teams to build, maintain, and improve reliable data pipelines and platforms that support reporting, analytics, automation, and decision-making.
Qualifications
B.E. / B.Tech / B.Sc. / BCA / MCA / M.Sc. / M.Tech in Computer Science, Information Technology, Data Science, Software Engineering, Computer Applications, Mathematics, Statistics, or a related discipline.
Freshers and experienced candidates are strongly encouraged to apply.
Candidates with 0–5 years of experience in data engineering, ETL development, database development, analytics engineering, software engineering, SQL development, or related technology roles can apply.
Candidates currently working as Data Engineer, Junior Data Engineer, Associate Data Engineer, ETL Developer, SQL Developer, Analytics Engineer, Database Developer, BI Developer, Software Engineer, or Data Analyst are encouraged to apply.
Candidates from IT services, SaaS, product companies, analytics, consulting, fintech, e-commerce, telecom, manufacturing, logistics, FMCG, or other industries are welcome.
Basic to good knowledge of SQL and relational databases.
Familiarity with MySQL, PostgreSQL, SQL Server, Oracle, or similar databases.
Basic to good programming knowledge in Python.
Understanding of ETL/ELT, data pipelines, data transformation, data modeling, and database fundamentals.
Familiarity with Pandas, NumPy, SQLAlchemy, PySpark, or similar data-processing tools will be beneficial.
Exposure to Airflow, dbt, SSIS, Informatica, Talend, Azure Data Factory, AWS Glue, or similar ETL/orchestration tools will be an advantage but is not mandatory.
Exposure to cloud platforms such as AWS, Microsoft Azure, or Google Cloud will be beneficial.
Familiarity with data platforms such as Snowflake, Databricks, BigQuery, Redshift, Synapse, or similar technologies will be an advantage but is not mandatory.
Basic understanding of data warehousing, star schemas, fact/dimension tables, data lakes, and analytical data models will be beneficial.
Exposure to Apache Spark, Kafka, Hadoop, or real-time data-processing technologies will be an advantage but is not mandatory.
Familiarity with REST APIs, JSON, CSV, Excel, files, and system integrations.
Exposure to Power BI, Tableau, Looker, Excel, or other BI tools will be beneficial.
Familiarity with Git, GitHub, version control, testing, debugging, and collaborative development workflows.
Exposure to Docker, CI/CD, DevOps, Linux, or cloud deployment will be an advantage but is not mandatory.
Understanding of data quality, data governance, security, access control, and documentation will be beneficial.
Good analytical, logical, debugging, troubleshooting, and problem-solving skills.
Good communication, documentation, and teamwork abilities.
Ability to work effectively with technical, analytical, and business teams.
Willingness to work in an on-site environment.
Internship, SQL project, Python project, ETL project, data-pipeline project, GitHub project, hackathon, dashboard project, or academic data project will be considered but is not mandatory.
Strong willingness to learn new data, cloud, ETL, database, and analytics technologies.

Work arrangement
No