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Lead Data Engineer Job in United States Recruiting by RBA, Inc.

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Lead Data Engineer

🔖 Full Time

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Lead Data Engineer RBA is an established leader and go-to partner for enterprise and mid-size organizations looking to transform their business through technology solutions. As a Digital and Technology consultancy, RBA brings a unique perspective to the conversation, considering technology capabilities and roadmaps and aligning with the business goals and objectives to drive innovative growth. In addition to working with some of the greatest companies in our market, RBA combines challenging career opportunities with a fun and exciting work environment and culture. We have numerous opportunities and are looking to expand our capabilities to deliver our clients' thought leadership and transformational solutions. If your expertise aligns with the qualifications below, let’s connect! We are open to fully remote employees and being hybrid and/or in office. We have offices in the beautiful downtown Wayzata, MN, area as well as downtown Duluth, MN where employees are welcome to work! Lead Data Engineer RBA is looking for a Lead Data Engineer to join our growing team. In this role, you will play a critical role in supporting pre-sales activities and client project engagements, working closely with both technical and non-technical stakeholders to design and implement data solutions that meet our clients' needs. You will be pivotal in architecting, developing, and maintaining robust data pipelines and systems. You will collaborate closely with cross-functional teams to design and implement scalable data solutions that align with our clients' business objectives. The ideal candidate will have a strong background in data engineering, a deep understanding of cloud technologies, and expertise in building efficient data architectures. We are seeking a highly skilled Data Architect to join our dynamic team. Responsibilities: Lead the design, development, and implementation of scalable and robust data architectures and pipelines. Provide technical leadership and guidance to project teams, ensuring best practices are followed throughout the development lifecycle. Evaluate and recommend emerging technologies and tools to enhance our data engineering capabilities. Conduct performance tuning, optimization, and troubleshooting of data infrastructure and processes. Collaborate with sales and consulting teams to understand client requirements and develop technical proposals and solutions. Mentor and coach junior team members, fostering a culture of continuous learning and growth. Key Skills and Qualifications: Bachelor’s or master’s degree in computer science, Engineering, or related field 8+ years of experience in data engineering, with a focus on designing and implementing data architectures and pipelines. Strong proficiency in programming languages such as Python, R, and SQL Extensive experience with cloud platforms such as AWS, Azure, or Google Cloud Platform Hands-on experience with big data technologies such as Apache Spark, Hadoop, and/or Databricks Familiarity with cloud data warehouse platforms, such as Snowflake Solid understanding of data modeling, ETL processes, and data warehousing concepts Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams and clients. Proven track record of successfully delivering complex data projects. Experience with visualization tools like PowerBI or Tableau Certifications in relevant technologies (e.g., AWS Certified Big Data - Specialty, Google Professional Data Engineer, Microsoft Certified: Azure Data Engineer Associate, etc.) Preferred Qualifications: Experience working in a consulting or client-facing role. Experience building AI-powered solutions aimed at driving business value. Familiarity with Azure AI services or similar machine learning and artificial intelligence platforms Experience implementing and optimizing data solutions on Azure, including Azure Data Factory, Azure Synapse Analytics, and Azure Databricks Experience working with Databricks for data engineering and analytics workflows. Familiarity with machine learning and AI techniques for data analysis and predictive modeling Familiar with Microsoft Fabric capabilities Experience with Microsoft development technologies.

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