Data Architect

JOB DESCRIPTION

Architect the Future of Enterprise Intelligence
The Senior Data Architect provides technical leadership across the company's data landscape shaping enterprise data strategy and designing scalable, secure, and well governed data platforms that power analytics, AI/ML, and intelligent applications. This role spans traditional data management (DBMS, data modeling, warehousing, governance) and modern cloud native/AI data engineering on AWS, including bronze, silver, gold patterns, Generation (RAG) for LLMs, and data products that serve Cloud-native SaaS application teams at global scale. You will collaborate with business stakeholders, data scientists, engineers, and platform teams to translate use cases into target data architectures, ensuring performance, reliability, security, and cost efficiency at global scale.

What You'll do
Modern Data Platform on One or More Cloud Platforms

• Architect end-to-end pipelines across from raw to polished layers using Cloud native services such as S3, Glue (ETL & Data Catalog), Lake Formation, Redshift, Athena, EMR/Spark, Kinesis/MSK, Step Functions, Lambda, EventBridge.
• Define storage/format strategies (e.g., Parquet/Delta/Apache Iceberg) and partitioning, compaction, and indexing for performance and cost.
• Implement row/ column level security, encryption (KMS), secrets management, and fine-grained authorization via IAM/Lake Formation.

AI/ML & Amazon Bedrock Data Foundations

• Design datasets and feature/knowledge layers to support SageMaker training/inference and Amazon Bedrock applications (e.g., Knowledge Bases, Guardrails, Agents, and Invoke Model/Converse orchestration).
• Lead RAG architectures (chunking, embeddings, retrieval) using vector databases such as Amazon OpenSearch Serverless (vector search) or Aurora PostgreSQL + pgvector; define evaluation and feedback loops to improve answer quality.
• Set prompt, context, and token budget standards; guide teams on safe data handling for LLMs (PII redaction, policy driven filters, secured context injection).

Tradition Data Architecture & DBMS Excellence

• Provide deep expertise in relational and NoSQL systems: SQL Server, PostgreSQL, MongoDB, including schema design, indexing, query/perf tuning, replication, partitioning, and HA/DR.
• Design and govern EDW/ Lakehouse/ODS patterns; integrate with .NET/C# services and Angular frontends via well designed APIs and data contracts.

Integration, Interoperability & Application Alignment

• Define API and data contract standards (REST/GraphQL, Protobuf/Avro/JSON), ensuring consistent versioning and backward compatibility for .NET/C# and Angular consumers.
• Orchestrate ingestion from SAP, Salesforce, IoT/telemetry, external data sources, and partner ecosystems; standardize CDC and streaming patterns (e.g., MSK/Kinesis, DMS, Glue).
• Partner with Solution/Platform Architects to ensure microservices and event driven designs are data efficient and observability ready.

Data Governance, Quality & Observability

• Implement data governance (policies, stewardship, data classification), cataloging (Glue Data Catalog), lineage (Open Lineage compatible), and quality (rules, thresholds, SLAs/SLOs).
• Embed monitoring & cost governance (CloudWatch, CloudTrail, Cost Explorer, Lake Formation audit, data access logs) and drive continuous optimization (storage tiers, compaction, pruning).

Security, Compliance & Risk

• Enforce privacy and compliance (e.g., GDPR) with data minimization, tokenization, masking, and access controls across environments.
• Define secure patterns for model inputs/outputs (LLM safety), prompt hygiene, and guardrails to prevent leakage or misuse.

Delivery Leadership & Collaboration

• Produce architecture blueprints, target state designs, and build/run guardrails; guide PoCs and pilots to derisk solutions.
• Mentor data engineers, analysts, and junior architects; lead design reviews, threat modeling, and cost/performance reviews.
• Communicate clearly with technical and nontechnical stakeholders, champion a culture of engineering excellence and learning.

What You’ll Bring

• This position is not eligible for employer-sponsored work authorization or visa sponsorship (including initial, transfer, or extension), and candidates must be authorized to work in the United States at the time of application and remain authorized for the duration of employment without the need for sponsorship.
• Bachelor’s or master's in computer science, Information Systems, Data Engineering, or related field (or equivalent experience). Relevant certifications a plus (e.g., AWS Data Analytics/Solutions Architect preferred).
• 10+ years designing and delivering enterprise data solutions, including hands-on work with both traditional DBMS and cloud native data platforms.
• 5+ years building on cloud platforms with production experience in several of: S3, Glue, Lake Formation, Redshift, Athena, EMR/Spark, Kinesis/MSK, Lambda, Step Functions, EventBridge, SageMaker.
• Demonstrated expertise implementing data propagation Lakehouse patterns and governance at scale.
• Proven track record supporting AI/ML workloads (feature stores, model data pipelines) and delivering RAG solutions with vector search on AWS.
• Strong SQL and Python; proficiency in data modeling - IFC (preferred), 3NF, dimensional/star, data vault, etc.
• DBMS: SQL Server, PostgreSQL (schema, indexing, query planning, replication/HA, partitioning, backup/restore).
• Data Engineering: Spark/EMR, Glue (ETL/ELT & Studio), Airflow/Step Functions orchestration, Parquet/Delta/Iceberg.
• Streaming/CDC: MSK/Kinesis, DMS (change data capture), event driven patterns.
• Security & Governance: IAM, KMS, Lake Formation, Secrets Manager, data masking/tokenization, RBAC/ABAC.
• AI/LLM enablement: Amazon Bedrock (Knowledge Bases, Guardrails, Agents), embeddings, chunking, retrieval, prompt design, token optimization, evaluation loops.
• Observability & FinOps: Cloud logs/metrics, lineage/quality SLAs, cost controls (storage/compute), workload rightsizing.
• DevOps/MLOps/IaC: Git, CI/CD for data pipelines; Terraform/CDK; environment promotion; artifact/versioning; blue/green or canary for data jobs.

Preferred Skills

• Experience with Redshift RA3/Spectrum, materialized views, workload management, and federated queries (Athena/Glue).
• Familiarity with Power BI / Microsoft Fabric and Amazon Quick Sight; semantic modeling and governance for BI.
• Exposure to privacy enhancing technologies (anonymization, differential privacy), policy as code, and guardrail frameworks.
• Experience working with geographically distributed teams and regulated data.
• Strategic thinking with the ability to balance short-term increments and long term architecture.
• Excellent written and verbal communication, facilitation of architecture decisions, and stakeholder alignment.
• Mentoring mindset and demonstrated influence without authority across cross functional teams.