Senior Data Engineer

Our prestigious $1B revenue per year client is seeking Senior Data Engineers to join their cutting-edge team, driving forward-thinking technology solutions for the future. This opportunity has the potential to convert into a salaried role.

The Senior Data Engineer is responsible for designing, building, and managing the data platform and tools to allow for the efficient processing and analysis of large data sets. Develops and maintains scalable data pipelines, ensures data quality, and deploys machine learning models to production. Collaborates with business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision-making across the organization. Builds real-time and batch pipelines to handle large volumes of data efficiently. Collaborates with cross-functional teams and translate business requirements into scalable data solutions.

Responsibilities:

• Design, develop, and maintain real-time or batch data pipelines to process and analyze large volumes of data. Designs and develops programs and tools to support ingestion, curation, and provisioning of complex first party and third-party data to achieve analytics, reporting, and data science. Design and develop Advanced Data Products and Intelligent API’s. Monitors the system performance by performing regular tests, troubleshoots, and integrates new features.
• Lead in analysis of data and the design the data architecture to support BI, AI/ML and data products.
• Designs and implements data platform architecture to meet organization analytical requirements. Ensures the solution designs address operational requirements such as scalability, maintainability, extensibility, flexibility, and integrity.
• Provide technical leadership and mentorship to team members. Leads peer development and code reviews with focus on test driven development and Continuous Integration and Continuous Development (CICD).

Requirements:

• Bachelor’s degree in computer science, information systems, data science, management information systems, mathematics, physics, engineering, statistics, economics, and/or a related field required.
• Master’s degree in computer science, information systems, data science, management information systems, mathematics, physics, engineering, statistics, economics, and/or a related field preferred.
• Minimum of eight (8) years of experience as a data engineer with full-stack capabilities
• Minimum of ten (10) years of Experience in programming
• Minimum of five (5) years in Cloud technologies like Azure, Aws or Google.
• Strong SQL Knowledge
• Experience in ML and ML Pipeline a plus
• Experience in real-time integration, developing intelligent apps and data products.
• Proficiency in Python and experience with CI/CD practices
• Strong background in IAAS platforms and infrastructure
• Hands-on experience with Databricks, Spark, Fabric, or similar technologies
• Experience in Agile methodologies
• Hands-on experience in the design and development of data pipelines and data products
• Experience in developing data ingestion, data processing, and analytical pipelines for big data, NoSQL, and data warehouse solutions.
• Hands-on experience implementing data migration and data processing using Azure services: ADLS, Azure Data Factory, Event Hub, IoT Hub, Azure Stream Analytics, Azure Analysis Service, HDInsight, Databricks Azure Data Catalog, Cosmo Db, ML Studio, AI/ML, etc.
• Extensive experience in Big Data technologies such as Apache Spark and streaming technologies such as Kafka, EventHub, etc.
• Extensive experience in designing data applications in a cloud environment.
• Intermediate experience in RESTful APIs, messaging systems, and AWS or Microsoft Azure.
• Extensive experience in Data Architecture and data modeling
• Expert in data analysis and data quality frameworks.
• Knowledgeable with BI tools such as Power BI and Tableau.
• Ability to work in a fast-paced, dynamic environment and manage multiple priorities effectively
• Excellent communication and collaboration skills
• Advanced understanding of data security best practices.
• Advanced understanding of systems and data integration architecture
• Critical thinking is a must.
• Problem-solving skills, including the ability to look for root causes and implementable, workable solutions, as well as process improvement ability.
• Proven ability to perform high-quality technical documentation and presentations.
• Excellent organization, time management, and communication skills.
• Ability to be an effective member of project teams.
• Demonstrate professionalism, flexibility/adaptability, and ability to multi-task and work in a team environment.