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.