Data Engineer Manager

Location: Bengaluru

About Us    Straive (formerly SPi Global) is a global leader in AI-driven value creation, business transformation, and Global Capability Center (GCC) delivery empowering private-equity portfolio companies, mid-market firms, and enterprises with scalable, technology-enabled execution. We operationalize Data Analytics and AI for global enterprises, working with several   Fortune 500 companies   .
We serve clients across industries, including Banking, Financial and Information Services, Retail, Media and Technology, EdTech, Science and Research, Logistics and Supply Chain, and Pharma & Life Sciences. Our strategically placed   team of 20,000+ employees   operates in nine countries: the Philippines, India, the United States, Nicaragua, Vietnam, the United Kingdom, Singapore, South Africa, and Canada.

Job Description
We are looking for a   Data Engineering Manager   to help our global clients solve complex data and analytics challenges and enable sustained digital transformation. You will work closely with diverse stakeholders to understand their strategic, operational, and commercial goals and translate them into scalable, robust, and future-proof data engineering solutions.
This role requires a strong balance of technical depth, client-facing leadership, and people management. You will be expected to drive data-driven decision-making across high-stakes engagements, institutionalize analytics capabilities, and build long-term client partnerships while continuously strengthening team performance.

Key Responsibilities
Strategic Delivery:
Lead and manage multi-disciplinary teams to design, develop, and deliver high-quality data engineering solutions across various industries.
End-to-End Ownership:
Own the delivery lifecycle of data engineering engagements, ensuring solutions meet client expectations regarding quality, scalability, timelines, and business impact.
Architectural Guidance:
Design, review, and guide scalable data architectures, automated pipelines, and sophisticated data models that support diverse business domains.
Stakeholder Management:
Manage complex client relationships, including requirement discovery, expectation management, and executive-level reporting.
Advanced Analytics Enablement:
Translate business goals into actionable data platforms and analytics-ready datasets to fuel AI, Machine Learning, and advanced reporting use cases.
Problem Solving:
Analyze complex, ambiguous business problems by synthesizing multiple data sources into clear, actionable recommendations for client leadership.
Operational Excellence:
Actively identify and resolve delivery bottlenecks, data integrity issues, or execution hurdles to ensure the team operates at peak efficiency.
Mentorship & Quality:
Uphold rigorous engineering standards, conduct code reviews, and mentor junior-to-mid-level engineers to foster a culture of technical excellence.
Required Tech Stack & Skills
Core Tech Stack:
Expert-level proficiency in   Python   ,   SQL   , and   Spark / PySpark   for distributed data processing.
Cloud & Data Platforms:
Hands-on expertise in at least two of the following:
AWS   ,   Databricks   ,   Snowflake   , or   Azure   .
Pipeline Mastery:
Deep experience building and managing ETL/ELT pipelines, orchestration workflows (e.g., Airflow), and performance optimization for large-scale datasets.
Architectural Depth:
Solid understanding of data modeling (Star/Snowflake schema, Data Vault) and scalable cloud-native architectures.
Analytical Rigor:
Strong ability to analyze complex ideas and develop structured, data-backed recommendations for non-technical stakeholders.
Stakeholder management:
Exceptional communication and   presentation skills   with a proven track record of building consensus among diverse stakeholder groups
Emerging Tech:
Familiarity with   GenAI   integration, MLOps, or data mesh/fabric concepts is highly desirable.
Governance:
Understanding of data governance, privacy (GDPR/CCPA), and data quality frameworks.
Required Education & Experience

Education:

Bachelor’s degree in a field such as Engineering, Computer Science, or a related technical field.

Experience:

7–10 years of overall experience in data engineering, analytics, or big data platforms.
Leadership:
4+ years of experience leading technical teams   and managing end-to-end client engagements.
Recognition & Achievements
We have been recognized as a Star Performer in Data & AI Services Specialists - Everest’s North America PEAK Matrix 2025, and as a Leader in AIM’s Pema Quadrant of Agentic AI Service Providers - 2025.
In Nov 2023, Straive acquired Gramener, an award-winning, design-led data science company, enhancing our data, analytics, and AI capabilities. In June 2025, we acquired SG Analytics, a leading provider of AI-powered insights and contextual analytics services.