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The Data Solutions Manager is responsible for leading the design, implementation, and optimization of scalable enterprise data architectures that support business intelligence, analytics, and digital transformation initiatives. This role ensures seamless integration of legacy systems with modern cloud-native platforms, promotes data governance and security, and drives the delivery of data solutions aligned with organizational goals. The incumbent will collaborate with cross-functional teams and stakeholders to build robust, future-ready data ecosystems within the banking and financial services environment.
Key Responsibilities
Solution Design & Architecture
Design end-to-end enterprise data solutions across customer, transactional, operational, and risk domains.
Develop reusable architecture blueprints and data integration patterns across multiple layers: ingestion, processing, semantic, and serving.
Evaluate and integrate open-source and vendor-based solutions into the data stack.
Platform Delivery & Implementation
Own delivery of data pipelines, data marts, APIs, and reporting interfaces that support business decision-making and automation.
Oversee DevOps/CI-CD practices for data deployments.
Lead PoCs and RFPs for emerging data technologies.
Standards, Governance & Security
Define architecture principles and data modeling standards (3NF, star schema, data vault).
Support Data Governance and Data Protection teams to ensure adherence to internal and regulatory data policies (e.g., GDPR, ODPC).
Ensure security protocols and data access controls are built into all solutions (RBAC, encryption, data masking).
Business Engagement & Stakeholder Management
Act as a technical advisor to business units, interpreting their needs and aligning them to technical solutions.
Present architecture decisions and trade-offs to non-technical audiences including senior executives.
Collaborate with Data Privacy, Risk, and Compliance to ensure solutions support operational and regulatory requirements.
Performance Monitoring & Optimization
Continuously monitor and optimize data pipelines, ETL jobs, and query performance.
Leverage observability tools to proactively identify system bottlenecks and incidents.
Recommend architectural changes to support growth, cost efficiency, and business agility.
Team Development & Leadership
Coach and mentor junior architects, engineers, and analysts.
Foster a learning culture within the data engineering team through knowledge sharing and technical training.
Help shape the long-term talent development plan for the data solutions team.
Qualifications & Experience
Bachelor’s degree in computer science, Information Systems, Data Science or related field.
Minimum 3–5 years of hands-on experience in enterprise data architecture, solution design, and delivery within banking or financial services.
Proven experience implementing scalable data platforms both on-premise and on cloud (AWS, Azure, GCP).
Strong familiarity with modern data stacks: ETL/ELT frameworks, data lakes (e.g., Hadoop/S3), data warehouses (e.g., Snowflake, Azure Synapse).
Experience leading cross-functional delivery teams and working with Agile/Scrum methodologies.
Experience integrating legacy core banking systems with modern cloud-native data solutions.
