Job Description Summary

Responsible for developing, testing and implementing data engineering solutions to generate analytical and reporting solutions. Responsible for analyzing and preparing the data needed for data science based outcomes. Also responsible for managing and maintaining metadata data structures besides providing necessary support for post-deployment related activities when needed. Design and build automations and incorporate low code-no code solutions to accelerate development cycle time.

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Job Description

Roles and Responsibilities

In this role, you will:

- Design and build automations and incorporate low code-no code solutions to accelerate development cycle time.
- Leverage technical data dictionaries and business glossaries to analyze the datasets.
- Perform data profiling and data analysis for any source systems and the target data repositories.
- Understand metadata and the underlying data structures needed to standardize the data load processes.
- Develop data mapping specifications based on the results of data analysis and functional requirements
- Perform a variety of data loads & data transformations using multiple tools and technologies.
- Build automated Extract, Transform & Load (ETL) jobs based on data mapping specifications.
- Validate the data mapping results and match with the expected results.
- Leverage/Implement Data Quality (DQ) rules provided.

Education Qualification:

Bachelor's Degree in computer science or equivalent with minimum 5+ years of hands on experience.

Desired Characteristics Technical Expertise:

- Ability to understand logical and physical data models, big data storage architecture, data modeling methodologies, metadata management, master data management & data lineage techniques.

- Hands-on experience in AWS services specially Redshift, Glue, RDS, Step Functions, S3, Sage maker, Kinesis.
- Hands-on experience in programming languages like Python. Unix
- Hands-on experience in writing SQL scripts for Oracle, MySQL, PostgreSQL.
- Experience in handling both Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) data models.
- Experience with data warehousing, Big Data. NRT - Kafka.
- Exposure to unstructured datasets and ability to handle XML, JSON file formats
- Exposure to Extract, Transform & Load (ETL) tools like Matillion Or Informatica.

-Exposure or experience in Databricks.

- Experience using 'Low code, No code' tools like Microsoft/Github co-pilot.

Domain Expertise:

- Exposure to handling enterprise ERP and CRM data.
- Knowledge of for industrial applications in a commercial/finance/manufacturing settings.
- Exposure to finance and accounting data domains.

Leadership skills:

- Partner with other team members to understand the project objectives and resolve technical issues.
- Communicate project status or challenges in a clear and concise manner to the cross team members.

- Ability to drive technical solutions to meet business outcomes.