Senior Data Engineer - Data Modeling & Warehousing (4-7 yrs)

Job Description :

This role is not for TopHire, we are currently hiring for a client. Looking for a Senior Data Engineer for a leading B2B food tech service provider.

As a Senior Data Engineer, your primary goal will revolve around creating and maintaining the infrastructure and tools necessary for collecting, storing, processing, and analyzing large volumes of data. In addition, possessing strong technical skills, leadership abilities, and a deep understanding of data engineering principles will keep you functioning a cut above the rest.

Responsibilities :

- Design and development of scalable data pipelines and ETL processes to process and transform large volumes of data efficiently.

- Define and implement data integration solutions to consolidate data from multiple sources into a unified view, ensuring data consistency and accuracy.

- Optimize data delivery and performance by implementing caching mechanisms, indexing strategies, and other advanced techniques.

- Collaborate with Data Analysts, Data Architects, and other stakeholders to understand data requirements and design data solutions aligned with business needs.

- Skilled in high data quality standards by implementing data validation and monitoring procedures.

- Continuously research and stay up to date with emerging data engineering technologies and industry best practices.

- Participate in code reviews, mentor, and guide junior data engineers, and contribute to the development of data engineering standards and best practices.

- Work closely with the product development teams to seamlessly integrate data engineering solutions into our products and services.

Qualifications :

- Bachelor's or master's degree in computer science, Information Technology, or a related field.

- 4-7+ years of hands-on work experience and a proven track record in data engineering, data architecture, or a related role.

- Proficiency in data modelling, data warehousing concepts, ETL processes and data processing techniques to transform and cleanse raw data.

- Programming skills in Python, SQL, Scala, Java, or any other programming languages used in data engineering.

- Extensive hands-on experience with data storage technologies such as Google Data Fusion, and Apache Data Flow, SQL databases (i.e., MySQL, PostgreSQL) and NoSQL databases (i.e. Cassandra, MongoDB etc.)

- Hands-on experience with cloud-based data solutions, such as AWS, Azure, or Google Cloud Platform for deploying and managing big data infrastructure.

- Possessing a working knowledge of data storage and visualization tools such as Google Looker, Power BI, and Tableau is an advantage.

- Proven expertise in Data Management/Architecture Practices, including Data Integration, Data Governance, Data Quality, Metadata Management, Data Security, and Data Encryption.

- Excellent problem-solving and analytical skills with strong communication and collaboration abilities.

- Demonstrated ability to lead and mentor a team of data engineers and drive projects to successful completion.