Senior Data Engineer

About the Role

Key Responsibilities

• Develop and deliver technological solutions to meet targeted business outcomes related to data management and ERP migration.
• Analyze, design, and develop enterprise data and information architecture deliverables, focusing on data as an enterprise asset.
• Follow reusable standards, design patterns, guidelines, and configurations to ensure consistent and valuable data delivery across the enterprise.
• Collaborate directly with stakeholders, including 84.51, to ensure data solutions meet project requirements.
• Utilize enterprise standards for data domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses.
• Leverage innovative technologies to renovate, extend, and transform existing core data assets, including SQL-based, NoSQL-based, and cloud-based platforms.
• Define high-level migration plans to bridge gaps between current legacy systems and future ERP solutions.
• Contribute to cost/benefit analysis for architectural decisions and analyze technology environments to identify deficiencies and recommend improvements.
• Promote reuse of data assets and manage the data catalog for reference.
• Draft architectural diagrams, interface specifications, and other design documents.
• Ensure clarity on ongoing projects and escalate issues when necessary, including collaboration with 84.51.
• Build data models and pipelines in data engineering environments, including Databricks, AWS, and Azure, with experience in legacy systems and new ERP rollouts.

Requirements

• Bachelor's Degree in computer science, software engineering, or a related field.
• Minimum of two technical disciplines such as data warehousing, big data management, analytics development, data science, APIs, data integration, cloud, servers and storage, or database management.
• At least 4 years of successful experience building complex data solutions delivered to customers.
• At least 4 years of proven experience delivering large-scale, high-quality operational or analytical data systems.
• At least 4 years of experience in data development principles, including end-to-end design patterns.
• Excellent oral and written communication skills.
• Deep knowledge of building data models and pipelines, with hands-on experience in Databricks, AWS, or Azure environments.
• Experience with data modeling, data integration, and working with legacy systems transitioning to new ERP solutions.
• Knowledge of cloud platforms such as Azure Data Lake, Data Factory, Databricks, and familiarity with tools like Python, Pyspark, SQL, EventHub, ADF, Synapse, and Data Catalog.

Nice to Have

• Experience with SSAS Tabular models, Power BI, Dataflows, and DAX.
• Experience building solutions using elastic architectures, preferably Microsoft Azure and Google Cloud Platform.
• Experience with SQL, NoSQL, and Big Data platforms.
• Experience with data science solutions or platforms.
• Experience with streaming technologies like Kafka, IBM MQ, and EventHub.
• Proficiency in Python, Spark, and SQL.
• Familiarity with Azure Data Platform stack: Azure Data Lake, Data Factory, and Databricks.

Benefits & Perks

• Comprehensive healthcare coverage including medical, dental, vision, and prescription plans.
• Flexible scheduling with paid time off, holiday, and sick pay based on eligibility.
• Free counseling through Employee Assistance Program and financial coaching with Goldman Sachs Ayco.
• Associate discounts on purchases including food, travel, and technology.
• Up to $21,000 in tuition reimbursement through Continuing Education programs.
• Opportunities for growth through industry-leading training and diverse career pathways.