Accolite

Data Architect – Payments (AWS & Streaming)

Posted On

Dec. 2, 2025

Location

Hyderabad, Telangana

Experience Level

10 - 15 Years Exp.

Job Type

Full Time

Apply By

Jan. 24, 2026

Job Description

Job Summary:

We are seeking a highly experienced Data Architect (Hands-On) to design and build the data backbone for Payments Data Products. This role is responsible for leading AWS lakehouse architecture, real-time streaming ingestion, data governance, observability, and operational excellence to support high-performance payment-status and analytics workloads.

You will architect, build, and optimize data products that support sub-10 ms payment-status lookups, real-time event ingestion, 7+ years analytical retention, and enterprise-grade governance.

Key Responsibilities
Data Products & Architecture

Own architecture for Channel Ops Warehouse (high-performance 30-day layer) and Channel Analytics Lake (7+ year retention).

Deliver status APIs and statement APIs with strict SLAs.

Architect AWS lakehouse using S3, Glue, Athena, Iceberg, and Redshift for BI/operational analytics.

Build dashboards using QuickSight for operations insights.

Streaming & Ingestion

Design resilient pipelines using Kafka / MSK / Kinesis for ISO 20022 lifecycle events (VPM/PMN/PSN).

Implement CDC, partitioning, retention, idempotency, replay, DLQ patterns, and event routing via EventBridge.

Event Contracts

Define event schemas using Avro/Protobuf, versioning strategies, and schema compatibility rules.

Migration (As-Is → To-Be)

Inventory existing APIs, file feeds, SWIFT, Aurora Postgres, Kafka topics.

Define migration plan, cutover waves, and runbooks.

Governance & Quality

Implement data-as-a-product practices, quality SLAs, lineage, retention rules, and access controls.

Observability & FinOps

Build dashboards (Grafana/Prometheus/CloudWatch) to track TPS, lag, throughput, success rate, and cost per 1M events.

Publish runbooks, alerts, and budgets.

Scale & Security

Architect for tens of millions of payments/day with multi-AZ/region patterns.

Implement encryption, tokenization, IAM least-privilege, and immutable audit trails.

Hands-On Build

Write production-grade code in Python / Scala / SQL.

Build ETL/ELT in Spark/Glue; orchestrate workflows via Lambda / Step Functions.

Implement IaC using Terraform and CI/CD using GitLab/Jenkins.

Ensure automated testing and code reviews.

Expected Outcomes / KPIs

p95 < 10 ms for payment-status API.

≥99.9% availability of data products.

<15 ms replication lag from Kafka for priority datasets.

≥98% schema conformance.

Cost per 1M events trending downward.

Must-Have Skills

Kafka/MSK/Kinesis; EDA, event ordering, replay, idempotency.

Avro/Protobuf + Schema Registry.

AWS data stack: S3, Glue, Athena, Redshift, Lambda, Step Functions.

Payments domain + ISO 20022 (PAIN/PACS/CAMT).

Data governance, lineage, retention, access control.

Observability & cost management (Grafana/Prometheus/CloudWatch).

Production-grade coding (Python/Scala/SQL).

Terraform, CI/CD, automated tests.

Data Architecture Fundamentals (Required)

Logical & physical data modeling, normalization (up to BCNF), denormalization strategies.

SCDs, partitioning, indexes, OLTP vs OLAP schema patterns.

CQRS, event sourcing, eventual consistency.

Event-driven design, bounded contexts, domain events.

Schema evolution strategies and domain-driven design concepts.

Preferred Skills (Nice to Have)

ksqlDB, Flink, Aurora internals.

Redshift performance tuning.

API gateways (Apigee/API-GW), mTLS, webhook patterns.

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