Data Engineer

The Data Engineer position requires analytical and design skills with the ability to translate user and system requirements into a data model and technical design.

Key Responsibilities:

Create ETL design documentation, Source-to-Target spreadsheets, and technical design specifications.

Provides technical expertise, troubleshoots, guides and supports during design, development, testing, production and post-production

Understand the source system, capture and document business rules

Analyze and propose changes to maximize code re-usability and maintaining business value

Develop, implement and maintain highly efficient and scalable ETL processes.

Provides expert technical knowledge and solutions pertaining to Data Integration.

Identify opportunities to optimize the ETL environment, implement monitoring, quality and validation processes to ensure data accuracy and integrity.

Provide inputs into data governance organization to drive the data governance charter.

Ensure compliance to internal standards and guidelines.

Conduct unit testing and component integration testing for solutions developed

Hiring Criteria:

A.Work Experience

Bachelors degree in an information technology field or Computer Science or related fields

Technically strong in ETL concept, design and development.

5- 7 years' experience developing medium to large complex Integration solutions using Informatica ETL

4+ years of experience with both hands-on and lead experience in providing data warehousing solutions

Strong SQL & PL/SQL skills with the ability to solve highly complex challenges

Basic technical experience and business knowledge in various SDLC methodologies including waterfall, iterative, agile software development life cycle or related disciplines/processes is preferred.

Good communication and interpersonal skills

Ability to communicate clearly in writing to document data requirements and translate into technical solutions.

Strong Spark & Hadoop/Cloudera skills.

2+ years development experience in JAVA framework.

B.Level of Knowledge

In-depth knowledge of ETL tools is preferred, e.g. Ab Initio, Informatica, and Data Stage.

Knowledge in DevOps tools such as Bitbucket for building code repository and Oozie and Airflow for batch execution is preferred.

Advanced technical and business knowledge in software development life cycle, quality assurance, project management and other related disciplines/processes.

Understanding of ETL design and development best practices.

Understanding of data governance, master data management best practices.

C.Competencies

Leadership

Strategic and Business Acumen

Decision Making and Accountability

Resourceful Planning and Organizing

Change management skills

Functional

Data Management/Programming

Presentation Skills/Ability to communicate findings to both business and IT

Collaborative Teamwork

Results Orientation

Inspiring self must possess intellectual curiosity to enjoy problem solving and ask the right questions to fully understand business rules