Senior Data Engineer

December 28, 2023

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Restaurant365

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Catering Software • Restaurant Operations Software • Restaurant Accounting Software • Restaurant POS Integration • Franchising Software

201 - 500

Description

• Participate in the overall architecture, engineering, and operations of a modern data warehouse and analytics platforms. • Design and develop the objects in the Data Lake and EDW that serve as core building blocks for the semantic layer and datasets used for reporting and analytics across the enterprise. • Develop data pipelines, transformations (ETL/ELT), orchestration, and job controls using repeatable software development processes, quality assurance, release management, and monitoring capabilities. • Partner with internal business and technology stakeholders to understand their needs and then design, build and monitor pipelines that meet the company’s growing business needs. • Look for opportunities for continuous improvements that automate workflows, reduce manual processes, reduce operational costs, uphold SLAs, and ensure scalability. • Use an automated observability framework for ensuring the reliability of data quality, data integrity, and master data management. • Partner closely with peers in Product, Engineering, Enterprise Technology, and InfoSec teams on the shared enterprise needs of a data lake, data warehouse, semantic layer, transformation tools, BI tools, and machine learning. • Partner closely with peers in Business Intelligence, Data Science, and SMEs in partnering business units to translate analytics and business requirements into SQL and data structures • Responsible for ensuring platforms, products, and services are delivered with operational excellence and rigorous adherence to ITSM process and InfoSec policies. • Adopt and follow sound Agile practices for the delivery of data engineering and analytics solutions. • Create documentation for reference, process, data products, and data infrastructure • Embrace ambiguity and other duties as assigned • Occasional travel may be required

Requirements

• 5-8 years of engineering experience in enterprise data warehousing, data engineering, business intelligence, and delivering analytics solutions • 1-2 years as the most senior technical member of a data engineering team • 1-2 years of SaaS industry experience required • Deep understanding of current technologies and design patterns for data warehousing, data pipelines, data modeling, analytics, visualization, and machine learning (e.g. Kimball methodology) • Solid understanding of modern distributed data architectures, data pipelines, API pub/sub services • Experience engineering for SLA-driven data operations with responsibility for uptime, delivery, consistency, scalability, and continuous improvement of data infrastructure • Expertise in understanding and translating business requirements into data/analytic solutions • Extensive experience with Agile development methodologies • Prior experience with at least one: Snowflake, BigQuery, Synapse, Databricks, or Redshift, preferably BigQuery • Highly proficient in both SQL and Python for data manipulation and assembly of Airflow DAG’s. • Experience with cloud administration and DevOps best practices on AWS and GCP and/or general cloud architecture best practices, with accountability cloud cost management • Experience supporting ML Ops • Strong interpersonal, leadership and communication skills, with the ability to relate technical solutions to business terminology and goals • Ability to work independently in a remote culture and across many time zones and outsource partners, likely CT or ET

Benefits

• This position has a salary range of $130,000-$170,000. • Comprehensive medical benefits, 100% paid for employee • 401k + matching • Equity Option Grant • Unlimited PTO + Company holidays • Wellness initiatives