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As a Software Data Engineer you will be responsible for data pipelines to work on both scheduled and real time use cases. Schedule pipelines run typically in Airflow and real time processing could be airflow or integrated querying in backend services.

Responsibilities

Work closely with team leads and backend developers to design and develop functional, robust data pipelines to support internal and customer needs

Write unit, integration, and DQA tests, and develop automation tools for daily tasks

Develop high quality, well documented and efficient code

Manage and optimize scalable pipelines in the cloud

Optimize internal and external applications for performance and scalability

Communicate regularly with project managers, quality engineers, and other developers regarding progress on long-term technology roadmap

Recommend systems solutions by comparing advantages and disadvantages of custom development and purchased alternatives

Key Skills

Domain Expertise

4-8 years of experience as a software/data engineer

Bachelor’s degree in Computer Science, MIS, or Engineering

Technical Skills

Advanced experience with relational database systems (RDBMS), with advanced proficiency in SQL for data querying, manipulation. Additionally complex data analysis, optimization, and performance tuning (MySQL, PostgresSQL, Amazon RDS).

Advanced proficiency with data integration and ETL (Extract, Transform, Load) processes to move and transform data between systems.

Experience (2+ years) with data pipeline orchestration tools like Apache Airflow for workflow management and automation.

In-depth knowledge of data warehouse design principles and best practices, including schema design, indexing strategies, and partitioning techniques.

Experience with analytical data stores and strong understanding of distributed computing principles (e.g., Spark, Presto, Pandas)

Advanced proficiency with cloud service technologies, ex: AWS (RDS, EC2, S3, Athena, Lambda)

Expertise in designing and optimizing data architectures for scalability, performance, and cost efficiency in cloud environments.

Experience with Docker container technology, familiar with kubernetes.

Experience with GIT (Gitlab preferred) source control systems

Familiarity with data governance, security, and compliance standards in cloud environments.

Experience with data visualization tools such as Tableau, Power BI, or Looker for creating interactive dashboards and reports

Mindset and attributes

Leadership and Mentoring skills to assist junior members of the data engineering team.

Proven track record of successfully completing end-to-end data projects from conception to implementation, including requirements gathering, design, development, testing, and deployment.

Strong problem-solving abilities to identify and resolve complex technical challenges in data processing and analytics.

Excellent project management skills to prioritize tasks, manage timelines, and deliver results within scope and budget constraints.

Effective communication skills to collaborate with stakeholders across different departments and levels of the organization.

Strategic thinking and ability to align data engineering initiatives with business objectives and organizational goals.

Continuous learning mindset to stay updated with emerging technologies, industry trends, and best practices in data engineering and analytics.

Nielsen is hiring a Senior Data Engineer - (Spark, Presto, Pandas, RDS, EC2, S3, Athena, Lambda)

Job Description

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Nielsen is hiring a Senior Data Engineer - (Spark, Presto, Pandas, RDS, EC2, S3, Athena, Lambda)

Job Description

Explore Biotech Careers

Salary Information

Create a Job Alert

Related Opportunities

Senior Manager, Product

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