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.