Data Architect

Job Title: Data Architect (10+ Years Experience)

Job Type:
Remote

Employment:
Full Time/ W2 (
NO C2C)

Job Description:
We are seeking a highly experienced
Data Architect
with 10+ years of expertise in designing, implementing, and optimizing large-scale data architectures across
cloud, on-prem, and hybrid environments
. The ideal candidate will have deep hands-on experience with
data modeling, data warehouse/lakehouse architecture, ETL/ELT design, data governance, MDM, metadata management, big data platforms, and cloud-native data solutions (Azure/AWS/GCP)
. This role requires strong analytical thinking, enterprise architecture mindset, and the ability to collaborate with cross-functional engineering, analytics, and business teams.

Responsibilities

• Architect, design, and implement
  enterprise-scale data platforms
  , including
  data lakes, data warehouses, lakehouse architectures
  , and real-time data systems.
• Define and govern
  data modeling standards
  using
  conceptual, logical, and physical models
  across OLTP, OLAP, and cloud-native systems.
• Design
  ETL/ELT frameworks
  and scalable ingestion pipelines using tools such as
  Azure Data Factory, AWS Glue, dbt, Informatica, Talend, SSIS
  , and
  Databricks
  .
• Lead architecture for
  cloud data ecosystems
  using
  Azure (ADF, ADLS, Synapse, Databricks, Fabric), AWS (S3, Redshift, Glue, EMR), or GCP (BigQuery, Dataflow, GCS)
  .
• Define and implement
  data governance, data quality, data lineage, metadata management, and MDM frameworks
  .
• Collaborate with engineering teams to implement
  data catalogs, business glossaries
  , and standardized documentation.
• Architect and support
  real-time and streaming data pipelines
  using
  Kafka, Event Hubs, Kinesis, Pub/Sub
  , or equivalent technologies.
• Evaluate and select
  RDBMS, NoSQL, distributed storage
  , and analytics platforms (SQL Server, Oracle, PostgreSQL, MongoDB, Cassandra, Snowflake, BigQuery, Synapse).
• Develop
  reference architectures, blueprint designs, best practices, API integration patterns
  , and data integration strategies.
• Ensure data platforms meet enterprise
  security, compliance, encryption, data masking
  , and access control standards.
• Work closely with
  Data Engineers, BI Developers, Analysts, Product Teams, and Business Stakeholders
  to translate business needs into scalable solutions.
• Lead performance tuning, optimization, and capacity planning for large-scale data environments.
• Provide architectural leadership and guidance during
  project planning, sprint planning, code reviews
  , and solution delivery.
• Stay current with emerging data technologies and recommend adoption strategies aligned with enterprise goals.

Required Skills:

• Strong hands-on expertise in
  data modeling
  (3NF, Star/Snowflake schemas, Data Vault, Dimensional Modeling).
• Experience architecting systems using
  Azure, AWS, or GCP
  , including:
• Azure:
  ADLS, ADF, Synapse Analytics, Databricks, Microsoft Fabric
• AWS:
  Redshift, Glue, EMR, S3, Athena
• GCP:
  BigQuery, Dataflow, Pub/Sub
• Strong expertise in
  SQL, Python, PySpark, Spark SQL
  , and distributed compute frameworks.
• Deep understanding of
  ETL/ELT methodologies
  , orchestration, and pipeline design.
• Knowledge of
  big data ecosystems
  : Hadoop, Hive, Spark, Delta Lake, Hudi, Iceberg.
• Experience with modern
  data warehouse/lakehouse architectures
  : Snowflake, Synapse, Databricks Lakehouse.
• Strong experience in
  data governance, MDM, metadata management
  , and data quality frameworks.
• Solid understanding of
  REST APIs, microservices
  , and integration architecture.
• Proficiency with
  CI/CD pipelines
  , version control (Git), DevOps tools, and automated deployment strategies.
• Strong understanding of
  security best practices
  including IAM, RBAC, encryption, data masking, and compliance (HIPAA, GDPR, PCI).
• Excellent communication, leadership, and architectural documentation skills.

Preferred Skills:

• Certifications such as:
• Azure Data Engineer / Azure Solutions Architect
• AWS Data Analytics Specialty / AWS Solutions Architect
• Google Professional Data Engineer
• Databricks Lakehouse Architect
• Experience with
  Master Data Management (MDM)
  platforms (Informatica MDM, Reltio, SAP MDG).
• Knowledge of
  BI & Analytics tools
  (Power BI, Tableau, Looker, Qlik).
• Experience with
  AI/ML platform integration
  (MLflow, SageMaker, Vertex AI).