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.