As a crucial member of a data-driven organization, the Data Engineer is responsible for designing, building, and maintaining systems to process, collect, store, and analyze large volumes of data.

Collaborating closely with business analysts and stakeholders, the role involves creating and maintaining scalable data pipelines, implementing data architectures, and optimizing extraction, transformation, and loading processes.

The Data Engineer ensures data quality and integrity, develops data ingestion and processing systems, and implements storage solutions.

Additionally, responsibilities include capturing data definitions, collaborating with cross-functional teams to address data issues, and translating complex data into business-relevant narratives.

The Data Engineer must demonstrate proficiency in conducting complex data analysis, integrating data from multiple sources, generating reports, and identifying opportunities for data quality improvements.
The Data Engineer must also possess soft skills to influence third parties for access to key resources.

• Design and construct data models for business needs.
• Build and manage data ingestion and processing systems.
• Implement databases and data lakes for efficient data storage.
• Ensure data accuracy through validation and cleansing techniques.
• Collaborate with cross-functional teams to address data-related issues.
• Work with clients and internal teams to define reporting requirements and create precise data models for key business metrics.
• Gather, cleanse, and perform ETL for data sources.
• Design models for ingestion into Power BI collaboratively.
• Analyze data using statistical techniques, generate ongoing reports.
• Test, validate, and integrate new data models into production reports and dashboards.
• Maintain existing in-production reporting products.
• Develop and implement databases, data collection systems, and analytics strategies.
• Acquire and integrate data from primary/ secondary sources, including third-party APIs.
• Conceptualize, design, test, and launch new data models and reports.
• Document requirements and define data model specifications.

• 3 years working with multiple enterprise level data sources for developing business intelligence reporting.
• Strong SQL skills for query development, stored procedures, and views.
• Experience with establishing ETL processes with existing or new data sources.
• Working knowledge of Azure Services: Azure Data Factory, Azure SQL, Azure Databricks.
• Working knowledge of Power BI, SSMS, Excel, DAX competency, and data gateways, Power Apps, Power Automate,
• Knowledge of big data technologies and traditional analytics systems.
• Ability to conceptualize, design, and develop precise data analysis methodologies.
• Clear communication of findings to peers, leadership, and stakeholders.
• Strong analytical reasoning skills with the ability to synthesize data from multiple sources.
• Functional understanding of data schemas, model design, warehousing concepts, and relational data modeling.