Analytics Engineer

Calix is currently hiring an experienced Analytics Engineer, with keen analytical skills, an eye for detail and solid understanding of business processes. We are looking for a candidate that is highly organized, good at troubleshooting, forward thinking, has good communication skills and is self-motivated to execute and deliver our data and analytics strategy for the future.This is a key role in the Analytics and Decision Science team, collaborating with other data and analytics team members and managers, where you will develop an intimate knowledge of our databases, work with our data engineering and dbt developers, our business intelligence analyst team, and other stakeholders across the company.

Responsibilities and Duties:

Translate business requirements into technical specifications, including data streams, integrations, transformations, databases, data warehouses, data models and metrics.
Defining the data architecture framework, standards, and principles, including data modeling, implementation, and data management for enterprise data warehouses, and advanced data analytics systems.
Defining reference architecture, which is a pattern others can follow to create and improve data systems.
Defining and owning data flows, i.e., which parts of the organization generate data, which require data to function, how data flows are managed, and how data changes in transition.
Collaborating and coordinating with multiple departments, stakeholders, partners, and external vendors.
Design and develop data models that support specific functional business processes and functions.
Develop diagrams representing key data entities and their relationships.
Communicate clearly, simply, and effectively in every aspect of the job.
Engage business owners, and data engineers to understand requirements and produce designs and data models that will meet those requirements in a way that factors in performance, availability, security, scalability, maintainability, and extensibility.
Collaborate with our data governance and data engineering team to develop and maintain a formal description of the data and data structures including the data models, data flow diagrams, data dictionaries, and technical metadata.
Research and maintain knowledge in emerging data technologies and solutions to solve business problems.
Mentor, coach and share knowledge with other team members throughout the technology and business organization.
Take ownership of development tasks and/or projects to see that “whatever it takes” is done to accomplish goals on time
Ability to quickly learn new and existing technologies with strong attention to detail and excellent analytical capabilities
Design mock-ups and wireframes, collaborating with business stakeholders on the functional requirements and Data Engineering on the technical specifications and solution design.
Design and develop business-friendly data sets (datamarts and semantic models).
Develop, standardize and improve documentation on data structures, models and transformations.
Build out datasets and set up monitoring, testing and automation for datasets.
Lead break fixes in the data pipeline.
Drive and own quality of data in datasets and data flowing through data pipelines.

Qualifications:

Proven experience in data architecture and refactoring complex systems, as an architect, team-leader or a senior team-member.
Solid understanding of data architecture and data modeling techniques.
Software, database development or BI experience.
Program Management experience.
Have worked in a organization that supported key processes like Demand and Supply, Quote to Cash, Procure to Pay, Market to Customer with transactional level data, key measures and metrics and report visualizations.
In depth understanding of data architecture, data warehouse modeling, data integration, data quality, master data management, data governance and other data services related to data warehouse environments.
Strong written and verbal communication skills.
Ability to work cross-functionally and interact effectively with all levels of the organization.
Ability to thrive in both individual and team environments.
Experience consuming/exposing data in various ways, including APIs, BI Tools, SQL, Python.
In-depth knowledge of a wide range of established and emerging data technologies.
Flexibility/adaptability with a can-do attitude, and an ability to react quickly to identified opportunities.
Appreciation for a culture of not taking ourselves too seriously while taking our work very seriously.
Bachelor’s degree or equivalent experience in Computer Science, Engineering, Management Information Systems (MIS), or related field.

Technical Qualifications:

Data Warehouse: Snowflake, Databricks, DuckDB
Transformation Tools: dbt, Matillion, Alteryx, Datameer, Snowflake Scripting and Javascript Procedures
Data Modeling Tools: Erwin, sqlDBM, ER/Studio
Semantic and Metrics Modeling Tools: dbt metrics, cube.js, AtScale, Mode, LookML, Azure Analysis Services
SQL IDE: Oracle SQL Developer, DBeaver, Visual Studio
BI and Data Visualization: Power BI, Tableau, Looker, Excel
Task and Project Management: Jira

Preferred Qualifications:

Data Ingestion Tools: Fivetran, Jitterbit, Alyx, Stitch
Data Governance and Cataloging Tools: Atlan, Datameer, Collibra

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