Position Overview

As a Data Engineer, you will play a crucial role in designing, building, and maintaining our data

architecture. You will be responsible for ensuring the availability, integrity, and efficiency of

our data pipelines, enabling our organization to make informed, data-driven decisions.

Responsibilities

 Data pipeline development: Design, build, and maintain scalable data pipelines for

ingesting, processing, and transforming data from various sources, ensuring data

quality, scalability, and reliability.

 Data modelling: Develop and maintain data models, architecture patterns, schemas,

and structures that support the needs of data analysts, data scientists, and other

stakeholders.

 ETL (Extract, Transform, Load): Create and optimize ETL processes to extract data from

diverse sources, transform it into usable formats, and load it into data warehouses or

other storage solutions.

 Data governance, quality and validation: Establish and enforce data governance

policies, standards, procedures, and best practices and implement data quality checks,

validation processes, and error handling to ensure the accuracy and consistency of

data.

 Performance tuning: Continuously monitor and optimize the performance of data

pipelines to meet business requirements and scalability needs.

 Data security: Implement and maintain data security measures to protect sensitive

information and ensure compliance with data privacy regulations.

 Collaboration: Work closely with data analysts, data scientists, and other stakeholders

to understand their data requirements and provide support in data access and

availability.

 Documentation: Maintain thorough documentation of data engineering processes,

data models, and data dictionaries.

 Stay informed: Keep up to date with emerging trends and technologies in data

engineering to ensure our data infrastructure remains cutting-edge.

Qualifications

 Bachelor’s degree in computer science, information technology, or a related field

 Demonstrable experience of minimum 7 years position as a Senior Data Engineer or

similar, with hands on experience in designing and implementing data lakes, data

warehouses, data modelling, ETL processes, and data transformation pipelines

 Experience in Azure cloud-based data platforms (e.g., Azure Synapse Analytics, Fabric,

Databricks etc.).

 Microsoft Fabric and Lakehouse experience is an added advantage for this role.

 Experience in real time data ingestion and streaming

 Proficiency in programming languages such as Python, Java, or Scala

 Strong knowledge of database systems (SQL and NoSQL), data warehousing, and big

data technologies

 Knowledge of data governance principles, data quality management, and regulatory

compliance

 Experience with orchestration services (i.e., Azure Data Factory (ADF), Azure Logic Apps,

Azure Functions, Databricks Jobs, Airflow etc.)

 Excellent communications, leadership, and collaboration skills

 Ability to work in a fast-paced, dynamic environment and lead multiple projects and

teams to deliver high-quality results

 Technical Expertise:

o Programming languages: Python, Java, Scala, and R.

o Data management & databases: Oracle, SAP, SQL, NoSQL, Data Warehousing

o Big data technologies: Apache Hadoop, Spark, Kafka, etc.

o Cloud platforms: Experience with Microsoft Fabric, Azure (Synapse Analytics,

Databricks, Machine Learning, AI Search, Functions, etc.), Databricks on Azure,

o Data governance: Experience with Data governance tools Ab Initio, Informatica,

Collibra, Purview etc.

o Data visualization: Familiarity with Tableau, Power BI

o DevOps & MLOps: CI/CD principles, Docker, MLFlow, Kubernetes

Benefits

 Competitive salary and benefits package.

 Opportunity to work on cutting-edge technology projects.

 Collaborative and innovative work environment.

 Professional growth and training opportunities