Data Engineer

Job Summary:

As a Data Engineer, you will spearhead the evolution of data pipelines—bridging the gap between legacy systems and modern cloud-based environments. You will implement our client’s data mart and customer analytics platform, and integrate data spanning on-premises Microsoft SQL Server and Google Cloud Platform services.

Duties/Responsibilities:

• Technical Solutions Architecture: Design and construct the technical architecture to support the solution. Define and implement architectural components, and develop data requirements, data maps, transformation rules, and aggregation plans. Define strategies for data extraction, hygiene, acquisition, and loading.
• Design & Build: Build scalable ETL pipelines utilizing Python, SQL Server, and SSIS alongside dbt and Airflow. Develop and optimize data warehousing solutions.
• Cloud Integration & Modernization: Oversee migration projects from legacy systems to GCP, and integrate and harmonize data across hybrid environments.
• Collaboration & Strategic Alignment: Work closely with Data Architects, Analysts, and stakeholders to ensure technical solutions align with strategic initiatives and client requirements.
• Quality & Process Improvement: Enforce data quality standards, and maintain comprehensive documentation.
• Performs other duties as assigned.

Required Skills/Abilities:

• Excellent verbal and written communication skills.
• Excellent interpersonal, negotiation, and conflict resolution skills.
• Excellent organizational skills and attention to detail.
• Excellent time management skills with a proven ability to meet deadlines.
• Strong analytical and problem-solving skills.
• Ability to prioritize tasks and to delegate them when appropriate.
• Ability to act with integrity, professionalism, and confidentiality.
• Strong strategic thinking skills with the ability to translate business needs into solutions
• Experience in managing organizational change initiatives.
• Ability to function well in a high-paced environment with multiple demands, shifting priorities, ambiguity, and rapid change.
• Proficient with Microsoft Office Suite, Google Suite, and related software.

Education and Experience:

• A technical degree or equivalent professional experience.
• 5+ years of data engineering, data warehousing, and business intelligence experience
• Advanced proficiency in Python.
• Extensive experience with Microsoft SQL Server, including T-SQL and SSIS.
• Expertise with dbt and Airflow.
• Proficiency in data models, ETL/ELT processes, and data warehousing concepts
• Knowledge of cloud pipeline orchestration and workflow tools, such as Google Cloud Composer.
• Ability to manage and integrate data across hybrid environments.