Job Title: Senior Data Engineer Reports To: Chief Information Officer
The Senior Data Engineer is responsible for designing, developing, and maintaining the data infrastructure and systems. This is a collaborative role, working closely with cross-functional teams to understand data requirements, implement data solutions, and ensure the reliability, scalability, and performance of our data pipelines.
Roles and Responsibilities
Design and develop scalable, efficient, and reliable data pipelines and ETL processes to process large volumes of structured and unstructured data. - ETL Tools?
Collaborate with stakeholders to understand data requirements and translate them into technical specifications and data models.
Architect, implement, and manage data storage and retrieval systems, including databases, data warehouses, and data lakes.
Optimize data pipelines and processes for performance, scalability, and data quality, ensuring timely and accurate data delivery.
Perform data profiling, validation, and cleansing to maintain data integrity and consistency.
Identify and resolve data-related issues, ensuring the accuracy and reliability of data.
Implement and maintain data governance practices, data security measures, and data access controls.
Stay up to date with the latest advancements in data engineering technologies and methodologies and evaluate the potential impact on our data infrastructure.
Mentor and provide guidance to data engineers, fostering their professional growth and development.
Collaborate with cross-functional teams to drive data-driven decision-making and provide actionable insights.
Communicate effectively with technical and non-technical audiences.
Compile and maintain clear and comprehensive documentation for all data products, services, and platforms.
Other duties as assigned.
Qualifications and Requirements:
Bachelor’s degree in computer science, Information Systems, or a related field.
Proven experience as a Data Engineer or similar role, with at least 7 years of experience in data engineering.
Strong programming skills in languages like Python, Java, .NET, with experience in data manipulation and transformation.
Proficiency in SQL and experience with relational databases (e.g., MS SQL, MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB) and common data formats (e.g., JSON, XML, CSV).
In-depth knowledge of data modeling, data warehousing, and data integration techniques and best practices.
Hands-on experience with big data technologies and distributed computing frameworks is highly desirable.
Familiarity with cloud-based data platforms (e.g., AWS, Azure, Google Cloud) and services.
Strong understanding of data quality, data governance, and data security principles.
Experience with data visualization tools (e.g., Tableau, Power BI) is a plus.
Excellent problem-solving and analytical skills, with a strong attention to detail.
Effective communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
Proven ability to work collaboratively in a team environment and lead technical initiatives.