Contractual deployment for 12 months (renewable, with possibility of being regularized by the client)

Location: Makati Set-up: Hybrid (3 days a week in the office)

The Data Engineer is a key figure that is responsible for develop algorithm to transform data into useful actionable information. Plays a critical role in ensuring that data is stored, processed, and utilized effectively, aligning with the company’s strategic goals. Create unique data infrastructure, running tests on the designs to isolate errors and updating systems to accommodate changes.

Key Responsibilities:

• Design and implement scalable and robust data pipelines to support analytics and data processing needs.

• Develop and maintain data architectures, including data lakes and data warehouses.

• Ensure data quality and consistency through data cleaning, transformation, and validation processes.

• Collaborate with data scientists and analysts to gather requirements and deliver data solutions that support business objectives.

• Optimize data retrieval and develop dashboards and reports for various user needs.

• Implement data security and privacy policies to comply with legal and regulatory requirements

• Responsible for managing data security and privacy, including implementing data security controls, such as encryption and access controls, to prevent unauthorized access to data.

• Assembling large, complex sets of data that meet non-functional and functional business requirements

• Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition

• Collaborate with cross-functional teams, and effectively communicate technical concepts to non-technical stakeholders.

• Passion for staying up to date with the latest trends, technologies, and best

practices in data engineering.

Qualifications:

Required Experience:

• 6+ years in data engineering field or ETL, 7+ years preferred

• Extensive knowledge of BI concepts (i.e. ETL, dimensional modeling, data warehouse design, dashboarding)

• Extensive knowledge of database query languages (i.e. SQL), database design, optimizing queries, internals knowledge of query planning

Tools:

• (Mandatory): SQL, Python, Azure Cloud Platform, MS SQL Server, Informatica, Apache Spark, Azure Data Factory

Please refer to job description.