Machine Learning Engineer

November 6

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Unreal Staffing, Inc

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Description

• Are you passionate about designing, building, and maintaining data pipelines that support robust data architectures and facilitate seamless data flow? • Do you excel in creating scalable solutions that empower data-driven decision-making? • If you’re ready to develop and optimize data systems that drive impactful analytics, our client has the perfect role for you. • We’re seeking a Data Engineer (aka The Data Pipeline Architect) to build and manage cloud-based data infrastructures that support analytical needs and operational efficiencies. • As a Data Engineer at our client, you’ll collaborate with data scientists, analysts, and software engineers to construct data pipelines and storage solutions that are both efficient and secure. • Your role will be critical in ensuring data systems are optimized for performance, reliability, and scalability. • Key Responsibilities: • Design and Implement Scalable Data Pipelines: • Develop and maintain data pipelines that support data ingestion, transformation, and integration using cloud technologies. You’ll automate data workflows and ensure the seamless movement of data between various systems. • Manage and Optimize Data Storage Solutions: • Architect and maintain data lakes and data warehouses using platforms like BigQuery, Redshift, Snowflake, or similar cloud-based solutions. You’ll ensure data structures are built for performance and scalability. • Collaborate with Data Teams for Strategy Development: • Work closely with data scientists, analysts, and business stakeholders to understand data requirements and align data solutions with business goals. • You’ll provide input on data models and storage strategies. • Ensure Data Quality and Reliability: • Implement and manage processes for data validation, error handling, and consistency checks. You’ll ensure the quality of data is maintained through robust testing and monitoring practices. • Develop and Automate ETL Processes: • Build ETL (Extract, Transform, Load) workflows to handle complex data transformations. You’ll automate data extraction and transformation to support efficient data integration and reporting. • Monitor and Maintain Data Infrastructure: • Use monitoring tools to track the performance and reliability of data systems. You’ll proactively identify and resolve potential issues to maintain system health and performance. • Optimize Data Processing and Resource Management: • Implement strategies for efficient resource allocation and cost-effective data processing. You’ll leverage parallel processing and cloud capabilities to enhance performance.

Requirements

• Required Skills: • Cloud Data Platform Expertise: Experience with cloud data platforms such as AWS (Redshift, S3, Glue), GCP (BigQuery, Dataflow), or Azure (Azure Data Lake, Synapse). You’re proficient in handling cloud-based data solutions. • Programming and Scripting Knowledge: Proficiency in Python, Java, or Scala for building data pipelines and data processing tasks. You can write clean, efficient code for automation. • ETL and Data Pipeline Management: Proven ability to develop, maintain, and optimize ETL processes that handle large volumes of data. You’re experienced with orchestration tools like Apache Airflow or Luigi. • SQL and Database Management: Strong ability to write complex SQL queries and work with relational and NoSQL databases. • Problem-Solving and Critical Thinking: Excellent problem-solving skills with a proactive approach to identifying and resolving data-related challenges. • Educational Requirements: • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. Equivalent experience in data engineering and cloud technologies may be considered. • Certifications in cloud data engineering (e.g., Google Professional Data Engineer, AWS Certified Big Data – Specialty, Microsoft Certified: Azure Data Engineer Associate) are a plus. • Experience Requirements: • 3+ years of experience in data engineering, with a proven track record of building and managing cloud-based data systems. • Experience with real-time data processing frameworks like Apache Kafka or AWS Kinesis is advantageous. • Familiarity with containerization and microservices architecture is a plus.

Benefits

• Health and Wellness: Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums. • Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year. • Work-Life Balance: Flexible work schedules and telecommuting options. • Professional Development: Opportunities for training, certification reimbursement, and career advancement programs. • Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources. • Life and Disability Insurance: Life insurance and short-term/long-term disability coverage. • Employee Assistance Program (EAP): Confidential counseling and support services for personal and professional challenges. • Tuition Reimbursement: Financial assistance for continuing education and professional development. • Community Engagement: Opportunities to participate in community service and volunteer activities. • Recognition Programs: Employee recognition programs to celebrate achievements and milestones.