Endava

Senior Data Engineer (Python, Azure)

Posted 5 Days Ago

Be an Early Applicant

Iași

Senior level

Software • Consulting

The Role

The Senior Data Engineer will collaborate with data scientists and analysts to design and maintain effective data pipelines, utilizing cloud services and technologies like Azure Data Factory and Databricks. Responsibilities include ensuring data quality, improving scalability and efficiency of pipelines, and resolving data-related issues.

Summary Generated by Built In

Company Description

Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change.
By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses.
From prototype to real-world impact - be part of a global shift by doing work that matters.

Job Description

Our data team has expertise across engineering, analysis, architecture, modeling, machine learning, artificial intelligence, and data science. This discipline is responsible for transforming raw data into actionable insights, building robust data infrastructures, and enabling data-driven decision-making and innovation through advanced analytics and predictive modeling.

Responsibilities:

Work together with data scientists and analysts to understand the needs for data and create effective data pipelines
Solution design, implement, and maintain data pipelines for data ingestion, processing, and transformation using could services and other technologies
Create and maintain data solutions including Azure Data Factory, Azure Synapse, Databricks/Spark, Polars/Pandas, Fabric
Implementing data validation and cleansing procedures will ensure the quality, integrity, and dependability of the data.
Improve the scalability, efficiency, and cost-effectiveness of data pipelines.
Monitoring and resolving data pipeline problems, ensuring consistency and availability of the data.

Qualifications

Proficient in Python and SQL
Strong experience with Relational and ideally NoSQL databases.
Knowledge of good data design principles (concepts such as Kimball and Star Schema), data warehousing concepts and data modelling.
Strong understanding of ETL/ELT processes.
Exposure to data monitoring and observability tools.
Relevant experience with Event-Driven Architecture
Good understanding of Agile ways of working