Junior 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 Junior Data Engineer for a full-time, on-site opportunity based in Morena, Madhya Pradesh, India.
The role is designed for fresh graduates and early-career technology professionals interested in data engineering, Python, SQL, ETL/ELT, data pipelines, databases, cloud platforms, data warehousing, analytics, automation, and modern data technologies.
The Junior Data Engineer will work closely with IT, software, analytics, finance, operations, production, supply chain, sales, and other business teams to collect, clean, transform, integrate, validate, and organize data while supporting reliable data pipelines, databases, reporting systems, dashboards, and enterprise data solutions.
The role may involve working with Python, SQL, Pandas, NumPy, relational databases, ETL/ELT processes, APIs, cloud platforms, data warehouses, data lakes, workflow orchestration tools, business intelligence platforms, and modern data-engineering technologies depending on project and business requirements.
Qualifications
B.E. / B.Tech / B.Sc. / BCA / MCA / M.Sc. / M.Tech in Computer Science, Information Technology, Software Engineering, Computer Applications, Data Science, Artificial Intelligence, Mathematics, Statistics, or a related discipline.
Fresh graduates and candidates with up to 2 years of relevant experience are strongly encouraged to apply.
Final-year students completing their degree and available for full-time employment may also apply.
Candidates with 0–2 years of experience in data engineering, data analytics, database development, ETL development, software development, business intelligence, data science, or related technology roles can apply.
Candidates currently working as Junior Data Engineer, Associate Data Engineer, Entry Level Data Engineer, Graduate Data Engineer, Data Engineer, ETL Developer, SQL Developer, Database Developer, Data Analyst, BI Developer, Analytics Engineer, Associate Software Engineer, or Junior Software Engineer are encouraged to apply.
Candidates from IT services, SaaS, product companies, technology, consulting, e-commerce, fintech, telecom, analytics, manufacturing, logistics, FMCG, or other industries are welcome.
Basic to good knowledge of Python and SQL.
Familiarity with Python libraries such as Pandas, NumPy, Requests, SQLAlchemy, or similar data-processing libraries will be beneficial.
Understanding of relational databases such as MySQL, PostgreSQL, SQL Server, Oracle, SQLite, or similar technologies.
Familiarity with SELECT statements, joins, subqueries, aggregations, views, indexes, transactions, schemas, and query development.
Basic understanding of data cleaning, transformation, validation, integration, profiling, and data-quality concepts.
Exposure to ETL/ELT processes, data ingestion, data pipelines, workflow automation, batch processing, or data transformation will be beneficial.
Familiarity with REST APIs, JSON, CSV, Excel, flat files, and common data-exchange formats will be advantageous.
Understanding of database design, normalization, primary and foreign keys, data modeling, schemas, and relational data structures.
Exposure to data warehouses, data lakes, data marts, dimensional modeling, fact tables, dimension tables, or analytical databases will be beneficial but is not mandatory.
Exposure to AWS, Microsoft Azure, Google Cloud, or similar cloud platforms will be considered an advantage.
Familiarity with Amazon S3, Redshift, Glue, Azure Data Factory, Synapse Analytics, Google BigQuery, or similar cloud data services will be beneficial but is not mandatory.
Exposure to Apache Spark, PySpark, Airflow, Kafka, dbt, Hadoop, Databricks, or similar data-engineering technologies will be considered an advantage but is not mandatory.
Basic understanding of batch processing, streaming, scheduling, workflow orchestration, and data-pipeline concepts will be beneficial.
Familiarity with Power BI, Tableau, Looker, Excel, or similar reporting and business-intelligence tools will be advantageous.
Exposure to Git, GitHub, version control, branching, pull requests, and collaborative development workflows will be beneficial.
Exposure to Docker, Linux, CI/CD, Jenkins, GitHub Actions, or similar DevOps technologies will be considered an advantage.
Basic understanding of data governance, data security, access control, privacy, data integrity, backup, and recovery concepts will be beneficial.
Exposure to machine learning, artificial intelligence, data science, predictive analytics, generative AI, or related technologies will be considered an additional advantage but is not mandatory.
Familiarity with APIs, automation scripts, reporting workflows, ERP, CRM, manufacturing systems, supply-chain platforms, or enterprise applications will be beneficial.
Familiarity with Agile, Scrum, Jira, SDLC, technical documentation, requirements gathering, or issue tracking will be advantageous but is not mandatory.
Good analytical, logical, troubleshooting, and problem-solving skills.
Good communication, documentation, collaboration, and teamwork abilities.
Ability to understand business and data requirements and contribute to reliable, scalable, maintainable, and accurate data solutions.
Willingness to work in an on-site environment.
Internship, academic project, Python project, SQL project, ETL project, data analytics project, database project, data pipeline project, Power BI project, GitHub project, hackathon, freelance assignment, startup project, or open-source contribution will be considered but is not mandatory.
Candidates without previous full-time data-engineering experience can apply.
Strong willingness to learn new data-engineering tools, cloud platforms, databases, programming languages, analytics technologies, and modern data practices.
Job Location: Morena, Madhya Pradesh
Employment Type: Full-time, On-site
Experience: Freshers & 0–2 Years

Work arrangement
No