Data Analytics Engineer

A Data Analytics Engineer is a highly skilled professional responsible for transforming raw data into insightful, actionable information through sophisticated data analysis and engineering techniques. This role involves the integration of data from multiple sources, cleansing and transforming data sets, and developing robust analytical solutions to support business decision-making. The engineer must have a deep understanding of data architecture, statistical analysis, and various data modeling techniques. They also collaborate closely with data scientists, business analysts, and IT teams to ensure that data-driven insights are efficiently delivered across the organization. A successful candidate will have strong problem-solving abilities, excellent communication skills, and a passion for driving data innovation.

Responsibilities:

• Design and implement scalable data pipelines to collect and process data from diverse sources.
• Develop and maintain databases and data structures for efficient querying and data retrieval.
• Work collaboratively with data scientists to deploy machine learning models into production environments.
• Create comprehensive data flow diagrams and documentation for technical and non-technical stakeholders.
• Optimize data processing systems for maximum speed and efficiency in data handling.
• Conduct data quality assessments and implement data validation and cleaning processes.
• Analyze large datasets to identify trends, patterns, and actionable insights for business stakeholders.
• Ensure data security and privacy compliance across all data handling operations.
• Provide technical guidance and mentorship to junior team members and interns.
• Monitor and troubleshoot data systems to ensure reliability and performance consistency.
• Stay updated with the latest trends and technologies in data engineering and analytics.
• Collaborate with cross-functional teams to integrate data solutions into broader business processes.

Requirements:

• Bachelor's or Master's degree in Computer Science, Data Science, or related field.
• Proven experience in data engineering, including data pipeline and ETL development.
• Proficiency in programming languages such as Python, SQL, and R for data manipulation.
• Strong understanding of data warehouse technologies like Snowflake, Redshift, or BigQuery.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Excellent problem-solving and analytical skills with attention to detail.
• Strong communication skills to convey complex technical concepts to stakeholders.