Leads and supervises the data development team with Data Engineers. They are responsible for following the data strategy in the Business Unit where they are assigned. From a coordination and management perspective, they guide the development team under their charge, identify risks, and ensure that their team achieves Digital House's performance indicators. They drive innovation, collaborate diligently with other Data Leads to establish code quality standards, promote regulatory compliance, security, and foster a data-driven culture.
Responsabilities:
- Receives requirements for Data Products and/or Solutions and is responsible for conducting Understanding sessions to identify the list of ingestions and/or processes necessary to add value to the business where they are assigned.
- Includes all involved areas in the Understanding stage to determine if the necessary inputs are available to address the requested requirements and to identify the viability of the Data Solution, as well as defining scoped scope to avoid rework due to incomplete definitions.
- Supports data engineers in reviewing estimates based on their expert judgment considering timelines from all involved areas (architecture, security, SRE, data governance, etc.), including deployment, and ensures that deliveries are of quality, on time, and in form, avoiding rework.
- Actively contributes to planning backlog tasks when a data project, product, and/or solution is authorized.
- Provides a sprint status report of the project and/or data solution to the business where they are assigned and ensures that deliveries are on time, in form, and with quality.
- Warns and informs the business of risks in a timely manner to mitigate them or propose contingencies.
- Reviews the efforts of the data engineers under their charge and provides guidance in case the development does not meet standards, guidelines, or best practices.
- Conducts rituals and weekly 1-to-1 follow-ups with the data engineers under their charge to assist them in case of doubts, to identify needs in meeting their performance, and to motivate adherence to best practices and compliance with guidelines.
- Diligently and proactively contributes to all phases of the data engineering lifecycle with Agile methodology, avoiding reworks and delivering on time, in form, and with quality.
- Analyzes and proposes technical solutions for data storage using best practices, standards, and data governance guidelines, data privacy strategies, security, and compliance.
- Ensures the continuity of digital data solutions, insights, dashboards, etc., to build and consolidate a Data-Driven culture.
- Collaborates and contributes to the development of monitoring processes and data quality metrics to ensure that the data used by the business is reliable, intact, and complete.
Experience and Requirements:
- 6+ years of experience in Data Engineering or related fields, with minimum 2 years in technical leadership, coordination, and guidance of data engineers or similar roles.
- Knowledge of software development life cycle (SDLC) methodologies.
- Able to manage people's performance.
- Assertive Communication with technical and business teams.
- Expert experience in Project Management with Agile methodology (Scrum or Kanban).
- Expertise in business vision (business domain), to sensitively identify how data contributes to the business.
- Able to effectively and exceptionally socialize the design of the data solution without supervision.
- Expert experience in collaborating on projects to achieve OKRs, warning of risks, and providing business value.
- Expert competence in transparently communicating project status.
- Determination to make decisions
- Assertive Communication with technical and business teams.
- Expert knowledge in Data Engineering Lifecycle (also known as Data Processing Lifecycle).
- Expert knowledge in data processing techniques: batch, micro-batch, near real-time, and real-time.
- Expert knowledge in understanding Architecture: Business, Solutions, Data, etc.
- Expert understanding and experience to contribute and implement data privacy strategies.
- Expert understanding and experience in implementing and maintaining robust data governance strategies.
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