Databricks / Delta Lake Tech Lead + Business Analyst

Tata Consultancy Services Limited; Taguig; Sur place; PHP 1 800 000 - 3 200 000; Plein temps

Résumé du poste

Tata Consultancy Services Limited is seeking a Databricks / Delta Lake Tech Lead + Business Analyst in Manila. The role combines data engineering leadership with business analysis to deliver scalable data solutions for financial services clients.

Responsibilities include designing end-to-end data pipelines, aligning requirements with technical design, and ensuring data governance and security. 15+ years in delivery and 10+ years in complex projects are typical expectations.

Qualifications

• 15+ years of application delivery experience in financial services.
• 10+ years managing complex projects involving digital or online-transaction solutions.
• Experience handling vendor and third-party SI engagements.
• Expertise in database technologies (SQL, NoSQL) and data warehouse platforms (Redshift, Snowflake).
• Experience with ETL tools and data pipeline frameworks.
• Willing to work in Ortigas or Makati.

Responsabilités

• Defines, prioritizes and allocates resources; tracks and provides status reports of work assignments, projects, and programs in support of the Data Engineering team.
• Lead design, development, and implementation of end-to-end automated data pipelines.
• Design and implement robust data architectures and data pipelines for large-scale data processing.
• Review business and technical requirements; ensure data integration platform meets requirements.
• Identify bottlenecks and optimize data processing and storage systems; implement data quality monitoring.
• Collaborate with data science, analytics and IT to align data engineering with organizational goals.
• Ensure compliance with data privacy regulations and implement robust security measures.

Connaissances

Analytical thinking

Stakeholder management

Communication

Outils

SQL

NoSQL

Redshift

Snowflake

ETL tools

Data pipeline frameworks

Description du poste

Databricks / Delta Lake Tech Lead + Business Analyst

• Defines, prioritizes and allocates resources; tracks and provides status reports of work assignments, projects, and programs performed in support of the Data Engineering team.
• Lead design, development, and implementation of end-to-end complex automated data pipeline system using common Big Data Tools.
• Design and implement robust data architectures and data pipelines for large-scale data processing.
• Review business and technical requirements and ensure the data integration platform meets requirements
• Identifying bottlenecks and optimizing data processing and storage systems for improved performance and efficiency implement monitoring and measurement of data quality as defined by business rules
• Collaborating with other departments such as data science, analytics, and IT to understand their data needs and requirements, and aligning data engineering efforts to support organizational goals and initiatives.
• Ensuring compliance with data privacy regulations and implementing robust security measures to protect sensitive data from unauthorized access or breaches.

Databricks / Delta Lake Tech Lead + Business Analyst

• 15 or more years of application delivery experience in the financial services industry
• 10 or more years of experience in managing complex projects involving the implementation of digital or online-transaction solutions
• Experienced in handling vendor and third-party SI engagements
• Expertise in database technologies (SQL, NoSQL, etc.) and data warehouse platforms (e.g., Redshift, Snowflake).
• Experience with ETL tools and data pipeline frameworks.
• Candidate must be willing to work in Ortigas or Makati.

Key Performance Metrics:

1. Requirements assessment — Ability to grasp and translate new requirements quickly and accurately on the first pass, minimizing repeated clarifications, revisions, and requirement-related rework

2. Delivery Commitment — On time delivery of committed milestones and approved requirements

3. Architecture and requirements quality — Full transparency to implementation from business requirements to implementation including solution designs, data models, and acceptance criteria. Designs should pass architecture, data governance, technical review

4. Engineering outcome quality — no critical design or security defects at production release, and agreed performance, reliability, and data-quality thresholds achieved.

5. Incident resolution: Incidents resolved within SLA and recurring incidents supported by root-cause remediation