JOB OVERVIEW

We are seeking a skilled Data Engineer to join our dynamic team. The ideal candidate will be responsible for designing, developing, and maintaining robust data pipelines and architectures that support our analytics and business intelligence initiatives. You will work closely with data scientists, analysts, and other stakeholders to ensure the availability and reliability of data across various platforms. This role requires a strong understanding of both traditional and big data technologies, as well as proficiency in programming and database management.

QUALIFICATIONS

• Proven experience as a Data Engineer or in a similar role with a strong focus on big data technologies.
• Proficiency in programming languages such as Java, Python, or Shell Scripting (Bash).
• Familiarity with Hadoop ecosystem components including HDFS, MapReduce, and Apache Hive.
• Knowledge of cloud services like AWS or Azure Data Lake is highly desirable.
• Experience with database management systems such as Microsoft SQL Server, Oracle, or any other relational databases.
• Strong analytical skills with the ability to interpret complex datasets effectively.
• Understanding of RESTful APIs for integrating different systems.
• Experience with analytics tools like Talend for data integration tasks is a plus.
• Ability to work collaboratively in a team environment while managing multiple priorities effectively. Join us in leveraging the power of data to drive strategic decisions and enhance business performance. We look forward to welcoming innovative thinkers who are passionate about transforming raw data into meaningful insights.
  Job Type: Full-time
  Pay: $127,515.70 - $140,000.00 per year
  Work Location: In perso

• Design, develop, and implement ETL processes to extract, transform, and load data from various sources into data warehouses.
• Collaborate with data architects and data scientists to create scalable data models that meet business requirements.
• Optimize database performance through effective database design and tuning.
• Develop and maintain data pipelines using tools such as Apache Hive, Spark, and Informatica.
• Utilize cloud platforms like AWS or Azure Data Lake for data storage and processing.
• Implement analytics solutions using Looker or similar BI tools to provide actionable insights.
• Write efficient SQL queries for data retrieval and manipulation across different databases including Microsoft SQL Server, Oracle, and others.
• Engage in model training activities to improve machine learning algorithms.
• Participate in Agile development processes to ensure timely delivery of projects.
• Document processes, workflows, and technical specifications for future reference.