Sales & Distribution Data Functional

Job Responsibilities

• Design, develop, and maintain ETL/ELT pipelines for data ingestion, transformation, and integration.
• Collaborate with business and analytics teams to define data requirements and translate them into technical solutions.
• Build and optimize data models to support BI tools, dashboards, and advanced analytics.
• Ensure data accuracy, consistency, and compliance with data governance policies.
• Automate data workflows and monitor pipeline performance for reliability and scalability.
• Work closely with data architects and functional teams to improve overall data ecosystem efficiency.

• Bachelor’s degree in Information Technology, Information Systems, or a related field (Master’s degree is a plus).
• Experience in data engineering, data transformation, or data integration roles.
• Fresh graduates are welcome.
• Proven experience designing, developing, and maintaining ETL/ELT data pipelines for structured and semi-structured data using tools such as dbt, Informatica, Talend, or Apache Airflow.
• Hands‑on experience with cloud-based data platforms:
  Snowflake, Databricks, Google Big Query, Amazon Redshift, or Azure Synapse.
• Strong proficiency in SQL and at least one programming language (Python, Scala, or Java) for automation and data manipulation.
• Experience integrating and preparing data for Business Intelligence tools such as Power BI, Qlik Sense, or Tableau.
• Collaboration with business analysts, functional teams, and data consumers to translate business requirements into technical data solutions.
• Exposure to version control systems (Git) and CI/CD workflows, ideally within an Agile development environment.

• ETL/ELT tools: dbt, Informatica, Talend, Apache Airflow
• Cloud data platforms:
  Snowflake, Databricks, Google Big Query, Amazon Redshift, Azure Synapse
• Programming: SQL, Python, Scala, Java
• BI Platforms:
  Power BI, Qlik Sense, Tableau
• Version control and CI/CD:
  Git, Jenkins

• Analytical Thinking – interpret complex data processes, identify root causes, and propose solutions.
• Business Acumen – translate functional requirements into technical data solutions that add measurable value.
• Communication – clear communication with technical and non‑technical stakeholders.
• Collaboration & Teamwork – work effectively within cross‑functional teams.
• Problem‑Solving Mindset – approach challenges systematically, balancing technical precision with business needs.
• Attention to Detail – ensure data accuracy and consistency throughout transformation and integration processes.
• Continuous Learning – stay updated with emerging data technologies, engineering frameworks, and best practices.