Must speak well and have great interpersonal skills
Any ETL tool will work
They will be working on the complete Azure stack (databricks, ADF, Synapse analytics, Power BI).
Working on the Digital Supply Chain Project
Description:
In this role you'll be a key asset to the Data Services team s by performing a variety of functions including:
- Data Pipeline Development: Design, build, and maintain scalable and efficient data pipelines to extract, transform, and load (ETL) data from various sources into the organization's data systems. This includes sourcing, cleansing, and transforming raw data to ensure data quality and integrity.
- Data Modeling and Architecture: Collaborate with data architects to design and implement data models that align with business requirements. Optimize database structures and schemas to support efficient data retrieval, processing, and analysis.
- Data Integration: Integrate data from different sources and systems, including databases, APIs, streaming platforms, and external data providers. Ensure seamless data integration across various platforms and applications.
- Data Warehouse Management: Manage and optimize data storage and retrieval processes in data warehouses or data lakes. Implement and maintain appropriate data partitioning, indexing, and compression strategies to enhance data accessibility and performance.
- Data Quality and Governance: Establish data quality standards, data governance policies, and data management best practices. Implement data quality checks, validation rules, and automated monitoring processes to identify and address data anomalies or inconsistencies.
- Performance Optimization: Identify and resolve performance bottlenecks in data processing and storage. Optimize data workflows, queries, and indexing strategies to improve system efficiency and reduce latency.
- Collaboration and Documentation: Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to understand data requirements and provide data engineering support. Document data pipelines, data dictionaries, and technical specifications to facilitate knowledge sharing and maintain data lineage.
- Data Security and Compliance: Implement data security measures, including access controls, encryption, and anonymization techniques, to protect sensitive data. Ensure compliance with data privacy regulations and industry standards.
What's my work style?
- Excellent written and verbal communication skills
- Relationship builder
- Flexible, collaborative approach to meet changing priorities and business needs
What experience do I need?
- Experience with data modeling, schema design, and data warehousing concepts.
- Strong knowledge of ETL tools and data integration techniques.
- Programming skills in languages such as Python, or Scala.
- Understanding of big data technologies and frameworks is a plus (e.g., Spark, Databricks, Kafka).
- Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration abilities.