Data Engineer

The Data Engineer is a key role within the organization, responsible for designing, building, and maintaining large-scale data pipelines and architectures that support our business growth and customer journey initiatives. The ideal candidate will have a strong technical background in data engineering, with experience in building scalable data solutions, managing big data, and ensuring data quality and integrity

Deliverables and Results:

Design, develop, and maintain large-scale data pipelines and architectures to support business growth and customer journey initiatives.

Write, interpret, and optimize complex queries across disparate data sources using SQL.

Ensure data quality, integrity, and security by implementing data validation, data cleansing, and data governance processes.

Design and implement graph database solutions to support complex data relationships.

Develop and maintain graph data models, queries, and APIs to support business applications.

Collaborate with data analysts and business stakeholders to understand data requirements and develop data solutions that meet business needs

Ensure data compliance with regulatory requirements and industry standards

Perform statistical analysis on various data sets to derive actionable insights to improve business

Manage data synchronization and transfer of internal databases

Translating data into useful insights to drive and solve critical business and inform operational decisions.

Ensure data integrity for reporting tables and source tables.

Work with business team to develop and implement data models, data visualizations, and reporting tools.

Automate and improve data quality and bring productivity to workflows related to data.

Develop and maintain technical documentation of data pipelines, architectures, and systems

Bachelor or master degree in computer science, Mathematics or Statistics major

Relevant applied work experience in quantitative analysis of at least 6-8 years

Ability to work with large amounts of data from disparate sources: collecting, consolidating, analyzing, and synthesizing

Strong problem-solving skills

Hands-on experience and in-depth technical knowledge of SQL programming

Hands-on experience with a self-serve BI tool (Tableau or others)

Experience with extracting and modeling datasets with database queries and environment (Hadoop/Spark)

Experience with programming languages (e. g. PySpark mandatory, Python).

Knowledge of graph data models, graph query languages (e. g. Cypher, Gremlin), and graph algorithms.

Experience with graph data integration, data migration, and data synchronization

Strong problem-solving skills, with the ability to work independently and collaboratively

Excellent communication and documentation skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Education:

Bachelor or master degree in computer science, Mathematics or Statistics major

Professional Background & Experience:
Relevant applied work experience in quantitative analysis of at least 6-8 years

Prior Knowledge:

Experience with programming languages (e. g. PySpark mandatory, Python).

Knowledge of graph data models, graph query languages (e. g. Cypher, Gremlin), and graph algorithms

Language Skills : HIVE, PYSPARK, PYTHON