Senior Data Engineer - AWS

Role Purpose:Nomo is looking for a hands-on Senior Data Engineer to build and operate AWS-native data platforms for a modern fintech environment.This role is for someone who enjoys owning the full engineering lifecycle: infrastructure, pipelines, security, observability, CI/CD, documentation, and production support. It is ideal for an engineer who understands fundamentals. We build directly with native AWS services, open source tooling, Terraform, Python, and SQL.What You’ll Do:Build and operate secure, scalable AWS-native data pipelines.Build event-driven architectures using EventBridge, SNS, SQS, Kinesis, and DynamoDB Streams.Own Terraform for data services and CI/CD dependencies.Own the medallion data lake structure with Hive and Apache Iceberg tables.Design table partitioning, deduplication, compaction, file sizing, retention, and optimization settings.Build data models using dbt-core.Build and maintain third-party API integrations with credentials security, secret handling, and credential rotation.Optimize Python and SQL for cost, latency, and operational reliability.Support data scientists with AI/ML infrastructure, curated datasets, pipelines, and lifecycle support.Own logging, metrics, alerts, and operational visibility using CloudWatch and Datadog.What We’re Looking ForStrong production experience as a Data Engineer, Senior Data Engineer, Cloud Engineer, or similar role.Ability to lead projects and work with other tech teams and external stakeholders.Strong ownership mindset across development, testing, deployment, monitoring, documentation, and support.Strong hands-on experience with AWS-native data services.Good understanding of serverless, queues, streams, retries, DLQs, idempotency, and replayability.Strong Terraform or Infrastructure as Code experience.Good understanding of IAM, least privilege, PII handling, and secure cloud engineering.Nice to HaveFintech, banking, or regulated industry experience.Experience supporting ML or AI infrastructure on AWS.Experience with LakeFormation tag-based access control.Experience with Datadog alerting and incident response.Libraries such as awswrangler, DuckDB, and PyIceberg should click!How You’ll WorkAWS-native first: build close to the platform without depending on heavy SaaS abstractions.Hands-on: comfortable writing code, Terraform, IAM policies, tests, and operational runbooks.Pragmatic: choose Lambda, Glue, DuckDB or PySpark based on the actual workload.Security-aware: treat PII, IAM, secrets, encryption, and auditability as core engineering responsibilities.Performance-conscious: care about memory, file sizes, S3 I/O, partitions, cost, and query performance.Collaborative: communicate clearly, define Done, test properly, and work well across teams.What Success Looks LikeTeams can move faster through reusable tooling, better deployment standards, and clearer operational practices.Pipelines are reliable, secure, observable, and cost-aware.Data lake layers are well structured, governed, and optimized.Iceberg tables are maintained with clear partitioning, deduplication, and compaction logic.CI/CD, monitoring, documentation, and operational support are part of every delivery.Why To Join NomoYou will work on meaningful data engineering problems in a fintech environment where the team owns the platform end to end. This is a role for someone who wants strong technical depth, and the opportunity to shape AWS-native data engineering practices without relying on black-box SaaS platforms.