DATA ENGINEER I

We are seeking a motivated and detail-oriented Junior Data Engineer to join our India-based analytics team supporting the Channel Business Unit. This early-career role is designed for someone with a strong technical foundation who is eager to build practical experience in data engineering, Databricks, SQL, Python, data quality, and BI-ready data product development. This role will support the development and maintenance of curated datasets, reporting tables, reusable data products, and data pipelines that enable faster and more reliable BI delivery across Channel BU. The Junior Data Engineer will work closely with senior data engineers, BI analysts, data product owners, governance teams, and business stakeholders to help prepare accurate, well-structured, and trusted data for dashboards, self-service analytics, and business performance reporting.

• Support the design, development, testing, and maintenance of data pipelines and curated datasets on the Databricks platform.
• Develop and maintain datasets for reporting, analytics, dashboards, and business performance tracking.
• Use SQL, Python, and PySpark to transform, validate, and prepare data for analytics.
• Assist in troubleshooting data pipeline and reporting issues.
• Follow established development, testing, and release management standards.

• Build and maintain reusable datasets for Power BI, Tableau, and other analytics tools.
• Partner with BI analysts to understand reporting requirements, KPIs, and business rules.
• Create reporting tables, views, and data marts to support dashboard development.
• Validate data accuracy and ensure reporting outputs meet business needs.

• Support the development of fact tables, dimension tables, reporting views, and curated data marts.
• Apply data modeling concepts such as star schema, keys, joins, dimensions, and measures.
• Perform data validation, reconciliation, and quality checks.
• Investigate and help resolve data discrepancies and reporting issues.
• Document data structures, business rules, and validation results.

• Write and optimize SQL queries for data extraction, transformation, and analysis.
• Use Python or PySpark for automation and data processing.
• Develop maintainable and well-documented code.
• Participate in code reviews and follow engineering best practices.

• Use Git for version control and collaboration.
• Follow team processes for code reviews, releases, and documentation.
• Gain experience working within AWS-based data environments.
• Support validation and migration activities involving Amazon Redshift and Databricks.

• Follow data governance, security, and documentation standards.
• Support data lineage, metadata management, and access controls.
• Work closely with data engineers, BI analysts, product owners, and business stakeholders.
• Participate in requirements gathering, testing, and release activities.
• Communicate progress, challenges, and data-related issues effectively while contributing to a collaborative team environment.

• Bachelors degree in Computer Science, Data Engineering, Data Science, Information Systems, Mathematics, Statistics, Business Analytics, or a related field.
• 0-3 years of experience in Data Engineering, BI, Analytics, Data Warehousing, or Software Development.
• Strong knowledge of SQL, including joins, aggregations, filtering, and data validation.
• Basic experience with Python for data processing, automation, or analytics.
• Working knowledge of Git and version control.
• Exposure to Databricks, cloud platforms, data warehouses, or analytics tools through work, projects, certifications, or internships.
• Understanding of data modeling concepts including fact tables, dimensions, keys, views, and reporting datasets.
• Strong analytical, problem-solving, and communication skills.

• Experience through internships, projects, or work with SQL, Python, Databricks, AWS, Redshift, Power BI, Tableau, or ETL processes.
• Databricks certification or related training.
• Exposure to AWS services and cloud data warehouses.
• Familiarity with PySpark and distributed data processing.
• Experience supporting reporting, dashboards, and data quality initiatives.
• Knowledge of commercial, sales, supply chain, inventory, marketing, or customer data domains.
• Master's degree is an advantage.

• Eagerness to learn modern data engineering tools and cloud technologies.

• Ability to develop SQL queries and use Python for data transformation and automation.

• Interest in building expertise in Databricks, AWS, and modern analytics environments.

• Focus on accuracy, validation, reconciliation, and issue resolution.

• Understanding of reusable datasets for Power BI, Tableau, and self-service analytics.

• Strong communication and teamwork skills with engineers, analysts, and business stakeholders.

• Self-motivated, accountable, and willing to learn while managing assigned responsibilities.

Success in this role will be measured by the ability to:

• Build and maintain trusted datasets for reporting and analytics.
• Develop reliable SQL and Python solutions.
• Support Databricks-based data engineering activities.
• Follow Git and development best practices.
• Improve data quality, documentation, and reporting reliability.
• Communicate progress, risks, and issues effectively.
• Expand technical expertise in Databricks, SQL, Python, AWS, and BI technologies

Values: Integrity, Accountability, Inclusion, Innovation, Teamwork