Data Architect (Cloud)

Role: Solution Architect / Data Engineer (Cloud)

Type: Yearly Renewable

Requirements

• Minimum 5 years of experience in data warehousing, big data, or advanced analytics solutions.

Databases & Data Management:

• Experience with databases (e.g., Oracle, MS SQL, MySQL, Teradata, Databricks).
• Expertise in data repository design (e.g., operational data stores, data marts, data lakes).
• Proficiency in data query techniques (e.g., SQL, NoSQL, Spark SQL).
• Hands-on experience with Databricks (Delta Lake, MLflow, Spark).
• Experience with Informatica Data Management Cloud (IDMC) for data integration, transformation, and governance.

Cloud Data & Analytics:

• Must-have: Strong knowledge of AWS cloud services (e.g., AWS Glue, Redshift, S3, Lambda, Kinesis, Athena, EMR).
• Experience in building and optimizing ETL/ELT workflows using AWS-native tools, Databricks, or IDMC.
• Understanding of event-driven architectures and microservices.

Data Analytics & Machine Learning:

• Data modeling experience (e.g., Star Schema, Snowflake Schema).
• Proficiency in Python/R for data transformation, analytics, and statistical computing.
• Hands-on experience with ML and AI frameworks for predictive modeling and healthcare analytics.
• Experience in data visualization tools (e.g., Power BI, Tableau).

DevOps & Security:

• Infrastructure as Code (IaC): Terraform, CloudFormation.
• CI/CD & DevOps best practices for data pipelines and cloud infrastructure.
• Identity and Access Management (IAM), security best practices, and data governance.

Soft Skills:

• Strong problem-solving and critical thinking skills.
• Ability to communicate complex technical solutions to non-technical stakeholders.
• Proven experience in working with cross-functional teams and managing multiple stakeholders.

Certifications (Preferred but not mandatory)

• AWS Certified Solutions Architect – Associate or Professional
• Databricks Certified Data Engineer
• Informatica IDMC Certification

Responsibilities

• Define, develop, and maintain blueprints, roadmaps, and reference architectures for data analytics infrastructure and services.
• Analyze new requirements, develop solutions, and manage solution delivery through acquisition or change control.
• Enhance cloud capability by designing and implementing cloud-based data analytics architectures and patterns.
• Lead data migration and modernization initiatives by leveraging AWS-native services, Databricks, and IDMC.
• Work closely with business leads and system owners to understand solution requirements and identify architectural patterns.
• Develop and implement automation playbooks for managing and scaling cloud services, containers, and applications.
• Ensure compliance with industry best practices, governance, and security guidelines for cloud-based analytics solutions.
• Collaborate with DevOps and other Data Engineering teams to define, implement, and optimize data pipelines, ETL/ELT processes, and data lakes.
• Assist in vendor management to ensure that contracted vendors deliver architecturally scalable and sustainable solutions.

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