Data Management Engineer

Key Responsibilities:

As a Data Management Engineer, you will be a crucial player in our data-driven decision-making process. Your role will involve developing, optimizing, and maintaining our business intelligence solutions, enabling stakeholders to access and utilize data for informed decision-making.

•  Data Collaboration: Collaborate with business units to understand their data needs and provide solutions that drive insights.
• Architectural Development: Design, construct, and maintain data architectures that align with business requirements and support data-driven initiatives.
• Data Acquisition: Oversee data acquisition processes, ensuring the seamless flow of data from various sources into our data ecosystem.
• Programming and Tool Utilization: Utilize programming languages and tools to create efficient and scalable data pipelines.
• Data Acquisition and Integration: Collaborate with cross-functional teams to integrate and centralize data from various sources into our business intelligence platform.
• Data Transformation: Implement ETL processes to transform raw data into usable formats for reporting and analysis.
• Data Quality Assurance: Identify and implement strategies to improve data reliability, efficiency, and quality.
• Data Modeling: Develop and maintain data models to support efficient data storage and enhance retrieval for reporting and analytics.
• Data Tool Development: Create data tools to empower data scientists and analysts in their pursuit of innovative solutions.
• Data System Enhancement: Work with data and analytics experts to enhance the functionality of our data systems.
• Dashboard Development: Design, develop, and maintain interactive dashboards and reports using tools like Power BI.
• Report Development & Automation: Design and create interactive and visually appealing reports, dashboards, and data visualizations using tools like Power BI, Alteryx, or similar.
• Performance Monitoring Optimization: Continuously monitor and optimize the performance of business intelligence solutions.
• Ad Hoc Analysis: Perform ad hoc data analysis to answer specific business questions and uncover actionable insights.
• Data Governance: Ensure data governance best practices are followed in reporting and analytics initiatives.

Business Knowledge/Technical Skills:

• Bachelor's degree in a related field (e.g., Business, Data Analytics, Computer Science).
• Minimum of 2 years of experience in business intelligence, data analysis, or a related role.
• Proficiency in SQL and experience working with relational databases.
• Excellent data visualization and storytelling skills
• Experience in Business intelligence reporting tools (e.g., Power BI, etc..)
• Experience in data modelling and report development.
• Strong analytical and problem-solving and analytical abilities.
• Excellent communication skills to convey complex data insights.
• Effective communication and collaboration skills.
• Ability to work collaboratively in a dynamic, cross-functional environment.
• Familiarity with data management best practices, data governance and data quality concepts.
• Experience in the insurance/financial industry is a plus.
• Experience with ETL and data pipeline tools (e.g., Informatics, Alteryx, SSIS) is a plus.
• Familiarity with cloud services (e.g., Azure, AWS) and big data technologies is a bonus.
• Experience in object-oriented/object function scripting languages like Python.

  For experience Data engineer with 4+ years:

• Working knowledge of message queuing, stream processing, and scalable 'big data' data stores.
• Experience building and optimizing 'big data' data pipelines, architectures, and datasets.
• Proficiency in big data tools such as Hadoop, Spark, and Kafka.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Familiarity with data pipeline and workflow management tools (e.g., Apache Nifi, Luigi, Airflow, Dagster, Databricks etc..).
• Expertise in object-oriented/object function scripting languages like Python, Java, C++, Scala.