Data Engineer

Vestel A.Ş.

Qualifications:

• Bachelor’s Degree in Mathematics, Software Engineering or related disciplines,
• Master's degree is a plus,
• Practical hands-on experience in any of Microsoft services such as Synapse, Azure Databricks, Azure Data Factory, Azure Data Lake V2, Azure Purview, and Power BI / Azure Analysis Service is a big plus,
• Excellent command of written and verbal English (second language will be an asset),
• Working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases,
• Good understanding of basic analytics and machine learning concepts,
• Expertise in building automated data pipelines for cleaning, preparing, and optimizing data for ingestion and consumption,
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets,
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement,
• They should also have experience using the following software/tools:

- Experience with big data tools: Hadoop, Spark, Kafka, etc.

- Experience with Data Flow, Data Pipeline and workflow management tools such as Airflow

- Languages: Python, SQL (noSQL in the near future)

- Databases: BW, Azure Data Factory[PP1]

- ETL : Azure Data Factory

- Libraries: Pandas, numpy, SQLAlchemy etc.

- Visualization tools: PowerBI, plotly

- Environment: We use Azure ML, Pycharm and mostly Jupyter but we're open to anything!

Responsibilities:

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements,
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources,
• Assist with data-related technical issues and support their data infrastructure needs,
• Manage end-to-end responsibilities from requirement definition, data processing to reporting and visualization,
• Develop dashboards and applications with no-code / low-code application tools,
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader,
• Work with data and analytics experts to strive for greater functionality in our data systems,
• Advising data science team on appropriate tooling for a particular solution based on your expertise in specific technologies,
• Contribute to ad-hoc strategic projects,
• End-to-end ownership of data quality in our core datasets and data pipelines.