AWS Solutions Architect

1. Client Engagement & Consulting
2. Deep Data Architecture / Engineering Expertise
3. Strong Problem-Solving & Techno-functional Thinking The ideal candidate is someone who has grown within consulting/service organizations, understands how to translate business problems into scalable data solutions, and is still close enough to technology to guide hands-on teams.

Key Responsibilities

1. Client Engagement & Consulting * Act as a trusted advisor to banking clients (business + technology stakeholders) * Lead: o Discovery workshops o Use case identification o Solution discussions and architectural reviews

• Translate business problems (risk, fraud, customer analytics, reporting) into data-driven solutions

• Drive stakeholder alignment across business, data, and engineering teams 2. Data Architecture & Engineering Leadership

• Design and own end-to-end data architectures on AWS, including: o Data lakes / lakehouse architectures o Batch + real-time pipelines o Data ingestion, processing, and consumption layers

• Define data models, governance frameworks, and architecture blueprints
• Provide hands-on guidance on: o ETL/ELT pipelines o Streaming (Kafka / Kinesis) o Analytics platforms (Redshift / Snowflake / Databricks)

1. AWS Cloud Architecture * Architect scalable and secure AWS environments using: o S3, Redshift, Glue, Athena, EMR o Lambda, ECS/EKS, Step Functions o API Gateway, EventBridge, Kinesis

• Ensure adherence to: o AWS Well-Architected Framework o Banking compliance (RBI / PCI-DSS / data security)

1. Problem Solving & Solutioning * Break down ambiguous business problems into structured solutions * Drive solution design with trade-off analysis (cost, performance, scalability) * Support: o Data modernization initiatives o Legacy-to-cloud transformations o Real-time analytics and reporting solutions

2. Delivery & Team Leadership * Mentor and guide data engineers, cloud engineers, and analysts * Ensure high-quality architecture implementation * Collaborate with offshore/onshore teams for delivery success * Drive best practices in: o Data engineering o DevOps & automation o Testing and observability

o Data Engineering (Spark, SQL, Python) o Data pipelines & ETL frameworks

• Deep expertise in AWS data stack: o Glue, Redshift, S3, EMR, Athena o Kinesis / Kafka for streaming

• Experience with: o Modern data platforms (Databricks / Snowflake preferred) Architecture

• Proven ability to: o Design scalable data architectures o Define data flows, models, and integration patterns

• Strong understanding of: o Batch vs real-time processing o Data governance & quality frameworks Consulting & Client Skills

• Experience in client-facing roles (consulting/services firms preferred)

• Strong ability to: o Lead discussions with business + tech stakeholders o Convert requirements into solution designs

• Excellent communication and storytelling skills Banking / Financial Domain (Preferred)

• Exposure to: o Risk, fraud, payments, reporting, regulatory systems

• Understanding of: o Data compliance and security in banking