Role: Senior Data Architect (6223009387_1)
Location: Plano, TX (Hybrid)
Duration: 12+ Months
Requirements:
We are seeking a handsâ‘on Data Architect to design and evolve an
AWS‘based data platform”spanning streaming ingestion (Kafka),
API/enterprise integration (MuleSoft), containerized data services
(EKS), data lake on S3, interactive query with Athena, and
analytics/reporting on Snowflake and Tableau.
You will set data architecture standards, lead solution design, and
guide engineering teams to deliver a scalable, secure, and cost
‘efficient platform that accelerates product and analytics use cases.
Responsibilities
• Architecture & Design Own the end to end data architecture across
ingestion, storage, processing, serving, and visualization layers.
Define canonical data models and domain data contracts; lead
conceptual/logical/physical data modeling and schema design for batch
and streaming use cases.
• Establish reference architectures and patterns for event driven and
API ‘led data integration (Kafka, MuleSoft). Design secure, multi
‘account AWS topologies (VPC, IAM, KMS) for data workloads; enforce
governance, lineage, and cataloging
• Platform Enablement (New Platform Build‘out) Lead the blueprint and
incremental rollout of a new AWS data platform, including landing ât raw
ât’ curated zones on S3, Athena for ‘hoc/interactive SQL, and Snowflake
for governed analytics and reporting.
• Define platform SLAs/SLOs, cost guardrails, and chargeback/showback
models; optimize storage/compute footprints.
• Partner with DevOps to run containerized data services on EKS (e.g.,
stream processors, microservices, connectors) and automate with CI/CD.
• Data Integration & Processing Guide ingestion patterns: Kafka
topics/partitions, retention, compaction, schema evolution
(Avro/Protobuf), DLQ strategies.
• Architect MuleSoft APIs/flows for system to ‘system data exchange and
orchestration; standardize API contracts and security. Define Athena
query strategies, partitioning, file formats (Parquet/ORC), and table
metadata practices for performance/cost. Set patterns for CDC,
bulk/batch ETL/ELT, and stream processing; select fit purpose
transformation engines.
• Analytics, Reporting & Self ‘Service Shape a semantic layer and
governed Snowflake models (data vault/star schemas) to serve BI and data
science. Enable business teams with Tableau dashboards, certified data
sources, and governance for KPI definitions and refresh cadences.
• Security, Governance & Quality Implement data classification,
encryption, access controls (RBAC/ABAC), masking/tokenization, and audit
trails.
• Establish data quality standards, SLOs, observability (freshness,
completeness, accuracy), and automated validation.
• Leadership & Collaboration Provide architecture runway, backlog
guidance, and technical mentorship for data engineers, API/streaming
engineers, and BI developers.
• Partner with Product, Security, and Compliance to align roadmaps,
standards, and delivery milestones.
• Produce decision records, diagrams, and guidance that make complex
designs easy to adopt.
Requirements:
• 8+ years in data architecture/engineering with 3+ years architecting
on AWS.
• Proven design of S3‑based data lakes with robust partitioning,
lifecycle policies, and metadata/catalog strategy.
• Hands‘on experience with Kafka (topic design, schema evolution,
consumer groups, throughput/latency tuning).
• Practical MuleSoft integration design (API ‘led connectivity,
RAML/OAS, policies, governance).
• Production experience with Amazon EKS for data/streaming microservices
and connectors.
• Strong SQL and performance tuning with Athena; expertise selecting
file formats/partitioning for cost/perf.
• Data warehousing on Snowflake (ELT, clustering, resource monitors,
security) and delivering analytics via Tableau.
• Mastery of data modeling (3NF, dimensional/star, data vault), data
contracts, and event modeling.
• Solid foundations in security, IAM/KMS, networking for data platforms,
and cost management.
Preferred Qualifications:
• Experience with schema registries, stream processing frameworks, and
change data capture. Background in data governance (catalog/lineage),
metadata automation, and compliance frameworks.
• Familiarity with and DevOps practices for data (pipeline CI/CD,
environment promotion, GitOps).
• Prior work enabling self ‘service analytics and establishing an
enterprise semantic layer. Tools & Technologies (Environment) AWS: S3,
EKS, Athena, IAM, KMS, CloudWatch, Glue/Lake Formation (as applicable).
• Streaming & Integration: Kafka (+ Schema Registry), MuleSoft.
Warehouse & BI: Snowflake, Tableau.
• Data Formats: Parquet/ORC/Avro/Protobu; partitioning/bucketing best
practices.
• Observability & Quality: Metrics, lineage, DQ checks, and alerting
(tooling per org standard).