Data Engineer

Roles & Responsibilities

* Primary skills/competency: Informatica IDMC/IICS, Databricks - Data Engineering, AWS Cloud

* Secondary skills/competency: Python – Pyspark

Responsibilities:

• · Manage the end-to-end migration process from informatica PowerCenter (CDI PC) to Informatica IDMC, ensuring minimal disruption to business operations.
  
  · Hands on experience in Informatica IDMC for creating mappings, workflows, setting up Secure Agents etc.
  
  · Integrate data from various sources, both internal and external, into AWS and Databricks environments, ensuring data consistency and quality, while leveraging Informatica IDMC for data integration, transformation, and governance.
  
  · Develop ETL (Extract, Transform, Load) processes to cleanse, transform, and enrich data, making it suitable for analytical purposes using Databricks' Spark capabilities and Informatica IDMC for data transformation and quality.
  
  · Monitor and optimize data processing and query performance in both AWS and Databricks environments, making necessary adjustments to meet performance and scalability requirements. Utilize Informatica IDMC for optimizing data workflows.
  
  · Implement security best practices and data encryption methods to protect sensitive data in both AWS and Databricks, while ensuring compliance with data privacy regulations. Employ Informatica IDMC for data governance and compliance.
  
  · Maintain clear and comprehensive documentation of data infrastructure, pipelines, and configurations in both AWS and Databricks environments, with metadata management facilitated by Informatica IDMC.
  
  · Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to understand data requirements and deliver appropriate solutions across AWS, Databricks, and Informatica IDMC.
  
  · Identify and resolve data-related issues and provide support to ensure data availability and integrity in both AWS, Databricks, and Informatica IDMC environments. · Optimize AWS, Databricks, and Informatica resource usage to control costs while meeting performance and scalability requirements.
  
  · Stay up to date with AWS, Databricks, Informatica IDMC services, and data engineering best practices to recommend and implement new technologies and techniques.

Requirements

• · Degree in Computer Science, Information Technology, Computer Engineering or equivalent
  
  · Minimum 4 years of experience in data engineering, with expertise in AWS or Azure services, Databricks, and/or Informatica IDMC.
  
  · Understanding and hands on experience in all phases of project lifecycle & has implementation involvement in at least 2 project cycles.
  
  · Experience in AWS Services focusing on ETL and data processing using ETL software: Informatica PowerCenter, IDMC, Informatica Cloud Data Integration for PowerCenter (CDI-PC), Informatica Data Engineering Integration (DEI)
  
  · Strong understanding of data integration concepts, ETL process and data quality management.
  
  · Accomplished in designing and implementing ETL data mappings, transformations, and workflows.
  
  · Evaluate potential technical solutions and make recommendations to resolve data issues especially on performance assessment for complex data transformations and long running data processes.
  
  · Strong in Business Intelligence data model design and proficient in BI software such as Oracle Analytics Server (OAS), Tableau.
  
  · Strong knowledge of Oracle SQL and NoSQL databases, equipped with key SQL Skillsets on databases such as Oracle, Teradata and MS-SQL Server.
  
  · Working knowledge on BI standard languages such as Python, Java, VBA
  
  · AWS Associate/AWS Professional/AWS Specialty certification is preferred.
  
  · Databricks certifications, IDMC certifications, Tableau Certifications are a plus.
  
  · Experience in healthcare industry, with broad understanding of healthcare business processes like patient administration, patient medical and non-medical services are a plus.

Tell employers what skills you have

Scalability
Oracle
Azure
Pipelines
Informatica
Data Transformation
ETL
Data Integration
Data Quality
Data Governance
Data Engineering
SQL
Python
Metadata
Java
Databases

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