Responsibilities:

Design and implement scalable and efficient data architecture solutions.
Collaborate with cross-functional teams to understand data requirements and translate them into technical specifications.
Develop and maintain robust ETL (Extract, Transform, Load) processes for large datasets.
Ensure the availability, reliability, and performance of data processing systems.
Design and optimize data models for efficient storage and retrieval.
Implement best practices for data warehousing and database management.
Utilize and stay current on Big Data technologies such as Hadoop, Spark, and related frameworks.
Implement solutions for processing and analyzing large volumes of data.
Implement data quality checks and validation processes.
Ensure data security and compliance with data protection regulations.
Collaborate with data scientists, analysts, and other stakeholders to understand analytics requirements.
Work closely with software engineers to integrate data solutions into applications.
Monitor and optimize the performance of data processing systems and queries.
Create and maintain comprehensive documentation for data engineering processes and systems

Qualifications:

Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
Proven experience as a Data Engineer, with a focus on designing and implementing data solutions.
Proficiency in programming languages such as Python, Java, or Scala.
Experience with Big Data technologies (Hadoop, Spark).
Strong SQL skills for data querying and manipulation.
Expertise in database management systems such as MySQL, PostgreSQL, or NoSQL databases.
Experience in designing and optimizing data models.
Strong knowledge of ETL processes and tools.
Excellent collaboration and communication skills to work effectively with cross-functional teams.
Strong problem-solving skills and the ability to troubleshoot complex data issues.
Demonstrated commitment to staying updated on emerging technologies and industry trends.

Sr. Data Engineer