Senior Engineer, Data & Analytics at Anaplan Inc Canada

, Virginia, United States -

Full Time

Start Date

Immediate

Expiry Date

06 Feb, 26

Salary

0.0

Posted On

08 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Orchestration, Data Warehousing, ETL Development, Python, SQL Querying, Google BigQuery, DataOps, Infrastructure as Code, Git, Database Performance Tuning, Load Testing, Data Migration, Model-Building, Agile, Scrum, Project Management

Industry

Software Development

Description

At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market. What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture. Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform. Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small. Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together! Your Impact We are seeking an experienced Data & Analytics Senior Engineer to design, build, and deploy complex data models in Anaplan and manage data warehousing projects, as well as build and deploy internal applications to support our technology lifecycle, service delivery, and collaboration tools. You will integrate data from SaaS sources like Salesforce, Adobe Analytics, Workday, and Splunk into Anaplan and Google BigQuery. You will also: Maintain the highest levels of development practices, including creating technical designs, writing clean, self-sustaining code, and managing system configurations. Implement and maintain DataOps practices, including managing data infrastructure as code (IaC) with Terraform and utilizing Git for version control. Work closely with analysts and business process owners to translate business requirements into technical solutions and present analysis results. Conduct Database Performance Tuning, Load Testing, Data Migration, and design efficient ETL/ELT processes. Drive projects to synchronize efforts and achieve business goals. Your Qualifications 8+ years in data orchestration, data warehousing, and ETL/ELT development. Proficient in Python (production-level scripting, understanding existing code, Pandas DataFrames, ReST API Calls). Proficient in SQL Querying; extensive experience with Google BigQuery and the broader GCP platform. Strong knowledge of database concepts. Proven experience developing and troubleshooting ETL/ELT processes. Exposure to ETL tools (e.g., Informatica is a plus) and understanding of ETL/ELT architecture, including Modern Data Architecture (Data Lake). Experience with Git for version control and Terraform for Infrastructure as Code (IaC). Familiarity with CI/CD principles. Strong troubleshooting skills are a must for identifying and resolving complex data issues. Model-building experience in Anaplan is highly valued. Project Management Experience working in an Agile/Scrum environment using tools like JIRA. Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB) We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day! We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation. Fraud Recruitment Disclaimer It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals. Anaplan does not: Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person. Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication. All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to people@anaplan.com before taking any further action in relation to the correspondence.

How To Apply:

Incase you would like to apply to this job directly from the source, please click here

Responsibilities

Design, build, and deploy complex data models in Anaplan and manage data warehousing projects. Integrate data from various SaaS sources and implement DataOps practices.