Entry Level 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 an Entry Level 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 professionals interested in data engineering, SQL, Python, ETL/ELT, data pipelines, data integration, cloud technologies, databases, analytics, reporting systems, and modern data-platform practices.

The Entry Level Data Engineer will work closely with software, IT, analytics, operations, production, supply chain, finance, sales, and other business teams to collect, process, transform, validate, integrate, and organize data for reporting, analytics, automation, dashboards, enterprise applications, and business decision-making.

The role may involve working with Python, SQL, Pandas, NumPy, relational databases, ETL/ELT pipelines, APIs, data warehouses, cloud platforms, Spark, Airflow, Kafka, Power BI, Tableau, Git, Docker, and other 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 Entry Level Data Engineer, Graduate Data Engineer, Junior Data Engineer, Associate Data Engineer, Data Engineer Trainee, ETL Developer, SQL Developer, Database Developer, Data Analyst, BI Analyst, Junior Data Analyst, Associate Data Analyst, Graduate Engineer, Associate Software Engineer, or similar roles 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 SQL queries, joins, aggregations, subqueries, views, indexes, transactions, stored procedures, and relational database concepts.
• Familiarity with MySQL, PostgreSQL, SQL Server, Oracle, SQLite, or similar relational database-management systems will be beneficial.
• Basic understanding of data cleaning, transformation, validation, profiling, standardization, deduplication, and data-quality concepts.
• Exposure to ETL/ELT processes, data pipelines, batch processing, data integration, workflow automation, or data migration will be advantageous.
• Familiarity with REST APIs, JSON, CSV, Excel, flat files, databases, and other common data sources will be beneficial.
• Basic understanding of data warehouses, data lakes, data marts, dimensional modelling, fact tables, dimension tables, and analytical data structures will be advantageous.
• Exposure to AWS, Microsoft Azure, or Google Cloud data services will be considered an advantage but is not mandatory.
• Familiarity with technologies such as Amazon S3, Redshift, Glue, Azure Data Factory, Synapse Analytics, Google BigQuery, or similar cloud data services will be beneficial.
• Exposure to Apache Spark, PySpark, Apache Airflow, Kafka, dbt, Hadoop, Databricks, or similar data-engineering tools will be advantageous but is not mandatory.
• Basic understanding of batch processing, streaming data, pipeline scheduling, orchestration, monitoring, and data-workflow concepts will be beneficial.
• Exposure to Power BI, Tableau, Looker, Excel, dashboards, reporting systems, or business-intelligence tools will be considered an additional advantage.
• Familiarity with Git, GitHub, version control, branching, pull requests, documentation, and collaborative development workflows.
• Exposure to Docker, Linux, command-line tools, CI/CD, or cloud deployment concepts will be beneficial but is not mandatory.
• Familiarity with data governance, data security, access control, data privacy, backup, recovery, and data-quality practices will be advantageous.
• Exposure to machine learning, artificial intelligence, generative AI, predictive analytics, or data-science workflows will be beneficial but is not mandatory.
• Exposure to ERP, CRM, manufacturing systems, supply-chain platforms, inventory systems, finance systems, or enterprise-data environments will be considered an advantage.
• Familiarity with Agile, Scrum, Jira, SDLC, technical documentation, requirements gathering, issue tracking, or project collaboration will be beneficial but is not mandatory.
• Good analytical, numerical, logical, troubleshooting, and problem-solving skills.
• Good communication, documentation, collaboration, and teamwork abilities.
• Ability to understand business and data requirements and contribute to reliable, structured, scalable, and maintainable data solutions.
• Willingness to work in an on-site environment.
• Internship, academic project, SQL project, Python project, ETL project, data-pipeline project, analytics project, database project, dashboard 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, pipeline technologies, analytics systems, and modern data practices.

Job Location: Morena, Madhya Pradesh

Employment Type: Full-time, On-site

Experience: Freshers & 0–2 Years