Data Engineer

Key Responsibilities

Collaborate across workstreams to support data requirements, including the development of reports and dashboards. Analyze and perform

data profiling

to identify patterns, discrepancies, and improvements in line with

Data Quality and Data Management

processes. Design and develop

end-to-end (E2E) data pipelines : ingestion, transformation, processing, and surfacing of data for large-scale applications. Automate data pipelines using

Azure, AWS data platforms, Databricks, and Data Factory . Translate business requirements into

technical specifications

for project design and delivery. Perform data ingestion in

batch and real-time

via file transfer, APIs, data streaming (Kafka, Spark Streaming). Develop ETL processes using

Apache Spark

to meet data transformation and standardization needs. Build data exports, APIs, and visualizations using

Power BI, Tableau, or other visualization tools . Ensure alignment with best practices in

data governance, security, and architecture . Qualifications & Experience

Bachelor’s degree in

Computer Science, Computer Engineering, IT, or related fields . Minimum

4 years’ experience

in

Data Engineering . Strong skills in: Programming & Data Engineering:

Python, SQL, Spark Cloud & Data Platforms:

Azure, AWS, Databricks, Data Factory Architecture:

Data/Solution Architecture, APIs Data Visualization Skills:

Power BI (preferred) or equivalent tools, DAX programming, data modeling, storytelling, and wireframe design. Business Analyst Skills:

Requirement analysis, data profiling, basic data model design, SQL programming, business knowledge. Knowledge of

Data Lake, Data Warehousing, Big Data tools, Apache Spark, RDBMS, NoSQL, and Knowledge Graphs . Strong

team player , with excellent analytical and problem-solving skills.

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