We are a forward-thinking organization committed to leveraging data to drive informed decision-making and strategic growth. Our team is passionate about using advanced analytics and cutting-edge technology to transform raw data into actionable insights. We are seeking a talented and experienced Analytics Engineer to join our team. This role is integral to developing and maintaining our data infrastructure, enabling us to extract maximum value from our data assets.
Job Summary: As an Analytics Engineer, you will be responsible for designing, developing, and optimizing data pipelines, transforming data into formats that can be easily analyzed, and supporting the creation of insightful reports and dashboards. You will work closely with data analysts, data scientists, and other stakeholders to ensure that our data infrastructure is robust, scalable, and aligned with business needs. Your expertise in complex SQL, business intelligence tools like Tableau, ETL processes, and platforms like Databricks will be critical to your success in this role.
Key Responsibilities:
- Data Pipeline Development: Design, build, and maintain scalable and efficient data pipelines using SQL, ETL processes, and tools like SSIS. Ensure that data is transformed, cleansed, and loaded into data warehouses and analytics platforms accurately and timely.
- Complex SQL Development: Write, optimize, and troubleshoot complex SQL queries to extract and manipulate data from various sources. Ensure that SQL code is efficient, maintainable, and aligned with best practices.
- Business Intelligence (BI) & Reporting: Develop and maintain interactive dashboards and reports using BI tools like Tableau. Collaborate with data analysts and business stakeholders to ensure that reports meet business requirements and provide actionable insights.
- Data Integration & ETL: Implement and manage ETL processes to integrate data from multiple sources into centralized data repositories. Use SSIS or similar tools to automate data extraction, transformation, and loading tasks.
- Data Modeling & Architecture: Design and maintain data models and database schemas that support efficient querying and reporting. Ensure that data models are optimized for performance and scalability.
- Databricks & Big Data: Leverage Databricks to process and analyze large datasets. Use Apache Spark or similar frameworks to develop and optimize data workflows and ensure data quality and reliability.
- Collaboration & Communication: Work closely with data scientists, analysts, and other stakeholders to understand data needs and translate business requirements into technical solutions. Communicate effectively to ensure alignment and successful project delivery.
- Data Quality & Governance: Implement data quality checks and ensure compliance with data governance policies. Monitor data pipelines and reports to identify and resolve data integrity issues.
- Continuous Improvement: Stay up-to-date with the latest industry trends and best practices in data engineering, analytics, and BI. Continuously seek opportunities to improve data processes, tools, and methodologies.
Qualifications and Experience:
Education: Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related field. A Master’s degree is a plus.
Experience:
- 3-5 years of experience in data engineering, analytics engineering, or a related role.
- Proven experience with complex SQL development and query optimization.
- Hands-on experience with business intelligence tools, particularly Tableau.
- Experience with ETL tools and processes, such as SSIS, and data integration techniques.
- Familiarity with big data platforms like Databricks and frameworks like Apache Spark.
Skills:
- Strong SQL skills with the ability to write, optimize, and maintain complex queries.
- Proficiency in developing and maintaining Tableau dashboards and reports.
- Solid understanding of ETL processes, data integration, and data warehousing.
- Experience with cloud platforms and big data tools, particularly Databricks.
- Excellent problem-solving skills and attention to detail.
- Strong communication skills, with the ability to translate technical concepts into business language.
- Ability to work independently and as part of a collaborative team in a fast-paced environment.
Preferred Qualifications:
- Experience with Python or R for data analysis and processing.
- Familiarity with data governance and data quality best practices.
- Experience with cloud data platforms such as Azure, AWS, or Google Cloud.