Data Engineer

Engineer New Data Solutions!

Do you have a passion for building the pipelines that transform raw data into actionable insights? Are you a skilled developer eager to collaborate and contribute to a data-driven future? We are seeking a talented Data Engineer to join our growing team!

Play a pivotal role in building and maintaining the infrastructure that empowers our data-driven decision-making. As a Data Engineer, you'll leverage your expertise in data engineering and programming to design, develop, and maintain data pipelines that efficiently collect, transform, and deliver data to our data scientists, analysts, and business users.

What You'll Do:

• Design and develop scalable data pipelines using technologies like Python, SQL, and frameworks such as Spark and Airflow.
• Extract, transform, and load (ETL) data from various sources (databases, APIs, log files, etc.) ensuring data quality and consistency.
• Design and implement data warehousing and data lake solutions for efficient data storage and retrieval.
• Develop and maintain automated data pipelines for continuous data flow and integration.
• Monitor and optimize data pipelines for performance and scalability.
• Collaborate with data scientists, analysts, and other stakeholders to understand data needs and implement effective solutions.
• Stay up-to-date with the latest advancements in data engineering technologies and best practices.

What We Offer:

• Competitive salary and benefits package
• Opportunity to work on challenging and impactful projects
• Collaborative and supportive work environment
• Continuous learning and development opportunities
• Vibrant and growing company culture
• The chance to be the behind-the-scenes hero, enabling data-driven decisions that shape our future
• 4+ years of experience in the data field (data analyst, database administrator, or similar) and a desire to grow
• Experience with SSIS, SSRS, and ETL pipelines
• Database scripting languages (e.g., T-SQL, PL/SQL)
• Cloud-based database management (AWS RDS, Azure SQL Database, etc.)
• High availability (HA) and disaster recovery (DR) solutions
• Cloud platforms (AWS, Azure, GCP) and their data services (S3, Azure Data Lake, etc.)
• Big data technologies (Hadoop, Spark, Kafka, etc.)
• Data version control and lineage management tools
• Docker and containerization technologies