Data Engineer (Cloud)_Contract

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 5 years of experience in 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.