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Senior Data Engineer

unlimited holidays - work from home

Remote:

Full Remote

Contract:

Full time

Salary:

120 - 150K yearly

Experience:

Senior (5-10 years)

Work from:

United States

Offer summary

Qualifications:

5-8 years in data engineering, 1-2 years as senior technical member, SaaS industry experience required, Proficiency in SQL and Python, Experience with cloud platforms.

Key responsabilities:

Lead enterprise data lake and data warehouse execution
Develop data pipelines and transformations (ETL/ELT)
Partner with stakeholders on data needs
Ensure platforms adhere to ITSM and InfoSec policies
Create documentation for data processes

Restaurant365 Computer Software / SaaS SME https://www.restaurant365.com/

201 - 500 Employees

See more Restaurant365 offers

Job description

Restaurant365 is a SaaS company disrupting the restaurant industry! Our cloud-based platform provides a unique, centralized solution for accounting and back-office operations for restaurants. Restaurant365’s culture is focused on empowering team members to produce top-notch results while elevating their skills. We’re constantly evolving and improving to make sure we are and always will be “Best in Class” ... and we want that for you too!

Restaurant365 is looking for a Senior Data Engineer to join our data warehouse team as a technical leader that enables the flow of information and analytics across the company. The Sr Data Engineer will lead the execution of the enterprise data lake, data warehouse, and analytic solutions. This is a key role on a highly visible team that will partner across the organization with business and technical stakeholders to create the objects and data pipelines used for insights, analysis, executive reporting, and machine learning. You will have the exciting opportunity to shape and grow with a high performing team and the modern data foundation that enables the data-driven culture to fuel the company’s growth.

How you'll add value:

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

What you'll need to be successful in this role:

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

R365 Team Member Benefits & Compensation

This position has a salary range of $120,000-$150,000. The above range represents the expected salary range for this position. The actual salary may vary based upon several factors, including, but not limited to, relevant skills/experience, time in the role, business line, and geographic location. Restaurant365 focuses on equitable pay for our team and aims for transparency with our pay practices.

Comprehensive medical benefits, 100% paid for employee

401k + matching

Equity Option Grant

Unlimited PTO + Company holidays

Wellness initiatives

#BI-Remote

R365 is an Equal Opportunity Employer and we encourage all forward-thinkers who embrace change and possess a positive attitude to apply.