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.
Requirements
Education & Experience:
- Degree/Master's in Computer Science, Information Technology, Computer Engineering, or equivalent.
- Minimum 10 years of experience in data architect, data warehousing, big data, or advanced analytics solutions.
Technical Skills:
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.
- Healthcare data governance and compliance knowledge is a plus.
Certifications (Preferred but not mandatory)
- AWS Certified Solutions Architect – Associate or Professional
- Databricks Certified Data Engineer
- Informatica IDMC Certification
