• Become a member of cross-functional product and data team and provide the team with analytics data
• Take an active part in plannings, sprints, reviews and retros of the product teams
• Understand business goals and convert them into data collection requirements
• Create implementation concepts and technical analytics specifications
• Implement the tracking through the tag manager required for accurate data collection
• Be in close alignment with future data peers to jointly optimize analytics
• Make data more reliable & understandable so products can adapt quickly to customer needs and requirements
• Working with the business to gather requirements and design data, models
• Build a single source of truth data warehouse in Redshift
• Work closely with data engineers 
• Collect data from various sources and design solutions to provide business value
• Use technologies such as AWS, Airflow, DBT, SQL and some Python
• Mentoring more junior team members

Skills: Analytics and Data Interpretation, Agile Methodology, Business Understanding, Technical Analytics, Tag Manager Proficiency, Collaboration and Communication, Data Warehouse and ETL, Programming and Scripting

• Support and contribute to the analytics layer of team's data environment to make data standardized and easily accessible to end users
• Integrate new data sources and build ingestion pipelines for the data warehouse
• Write production-quality ELT/ETL data transformation code with an eye for performance, maintainability and scalability
• Help bridge the gap between understanding business needs and knowing how to design efficient, usable data models
• Diagnose and fix data discrepancies and maintain transparent code to ensure business requirements and consistent ETL logic
• Collaborate with stakeholders in growth marketing, merchandise planning, digital product, and finance & operations departments to define business questions and identify opportunities for data-driven improvements
• Build and maintain dashboards in Looker to deliver insights and help non-technical stakeholders be able to regularly track KPIs
• Document and communicate data insights and recommendations to stakeholders across the company and advocate for a data-driven culture internally and externally
• Development of new algorithms to automate the calculator of various KPIs, mostly focused on production data and Work Orders
• Can be automated periodic reports (e.g. a monthly report for the client) or ad-hoc (e.g. study of an anomalous condition on a solar plant).
• Maintenance of current code repository and documentation of existing and new algorithms and programs.

Skills: Data Integration and Pipeline Development, ELT/ETL Data Transformation, Data Modeling, Data Quality and Diagnostics, Stakeholder Collaboration, Dashboard Development, Communication and Advocacy, Algorithm Development 

• Develop data visualizations using business intelligence tools
• Utilize statistical or machine learning techniques to assess customer performance and potential
• Affinity towards problem solving and ability to perform difficult analytical tasks with limited supervision
• Develop and maintain products that deliver insight through data visualizations to enable users to grasp concepts, identify patterns, and take action to exceed client targets
• Embrace continuous integration and continuous delivery to add features quickly while maintaining solution stability
• Focus on producing statistical outputs and charts, can also explain what they mean and their implications
• Design, develop, test, implement, and support an analytical data infrastructure
• Interface with other teams to extract, transform, and load data from a wide variety of data sources
• Collaborate with functional leads to recognize and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
• Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
• Explore and learn the latest data engineering technologies to provide new capabilities and increase efficiency
• Perform source data analysis and qualification for inclusion into the Operations Data Lake
• Create metadata dictionaries, data flows and other critical documentation

Skills: Data Visualization, Statistical/Machine Learning, Problem Solving/Analytics, Product Development/Maintenance, Continuous Integration/Delivery, Communication, Data Infrastructure Development, Collaboration/Best Practices

• Perform analysis on operating the solar and storage power plants using conclusions to drive more accurate modeling and corrective actions for underperforming plants.
• Create streamlined and repeatable methods to analyze solar and storage operational data to enable regular analysis updates to be performed.
• Work with Asset Optimization stakeholders (Performance & Reliability Engineering, Asset Management, Site Managers) to coordinate analyses, corrective actions/follow-ups, and conclusions.
• Disseminate analysis conclusions to key stakeholders and management.
• Prioritize analyses based on impact and value to the business.
• Perform advanced data analysis, leveraging existing and novel methods to derive conclusions and actions from data.
• Opportunistically identify ways to leverage data analysis and/or studies to create value and see them through completion.
• Stay abreast of publications, industry developments, industry tool developments, software programming packages

Skills: Data Analysis Skills, Modeling Skills, Method Development, Stakeholder Management, Communication Skills, Prioritization Skills, Innovative Thinking, Continuous Learning

• Maintain contact with EDF R&D to further collaboration and ensure the best tools and methods are being used.
• Develop and maintain a highly reliable data pipeline for EDF R Test Facilities and ensure data recovery is high, data is backed up, and prepared for analysis.
• Ensure EDF R Test Facilities are operating through manual and/or automated checks, escalating downtime issues to EDF R O&M or accordingly.
• Lead and/or assist in design of experiment and data analysis.
• Develop, improve and maintain tools and software to help the Solar and Storage Engineering team operate more efficiently by automating and/or streamlining processes.
• Increase the capability and accuracy of the Solar and Storage Engineering team through the development of improved tools and methods.
• Collaborate with other groups to streamline interdepartmental workflows and to increase the value offered by Solar and Storage Engineering group deliverables.
• Develop tools and software to help the Solar and Storage Engineering team overcome operational challenges.

Skills: Technical Proficiency, Communication Skills, Project Management, Problem-Solving Abilities, Attention to Detail, Team Leadership, Adaptability and Innovation, Interdisciplinary Collaboration

• Experience working with customer acquisition, mobile, gaming, or finance domains
• Experience in cloud-native technologies
• Experience working with Tableau or equivalent
• Background in software development
• Working knowledge of streaming technologies (Kafka, NATS, etc) as well as cloud native distributed systems
• Knowledge of data orchestration tools such as Airflow 
• Experience or working knowledge of data warehousing systems e.g. Snowflake, Athena/Presto
• Ability to work both independently and collaboratively with cross-functional teams
• Excellent oral and written communication skills
• Basic knowledge of business practices.
• Must be knowledgeable of and comply with Client Privacy Policy, HIPAA regulations and E&O procedures and policies.
• Proficient in SQL, Python, and R
• Experience in providing data support or conducting analytics. 

Qualifications: BA in Computer Science with 3 years of Experience

• Eagerness to learn new technologies and technology tools.
• Results-driven/detail-oriented.
• Strong analytical, quantitative, and problem-solving abilities
• Experience writing SQL
• Experience wrangling dirty data from multiple sources to create a clean data model.
• Knowledge of best ways to model Marketing, Product, and Financial data.
• Thorough knowledge of relational database and data warehousing theory and practice
• SQL data modeling, Git and CI/CD best practices
• AWS or GCP development and operations experience (EMR, Spanner/Redshift/BigQuery, S3/GCS, data pipelines, etc.)
• Experience working with an analytics team
• Experience with autoML platforms (H2O, DataRobot, Google autoML, etc.)
• A solid math and statistics background
• Ability to interpret a variety of instructions furnished in written or oral form

Qualifications: BS in Data Science with 2 years of Experience

• Hands-on experience with Snowflake development/implementation
• Experience developing ETL, ELT and Data Warehousing solutions
• Experience developing SQL scripts and stored procedures that process data from databases
• Experience with batch job scheduling and identifying data/job dependencies
• Strong understanding of various data formats such as CSV, XML, JSON, etc.
• Experience with Snowflake cloud-based database.
• Experience with Snowflake SnowSQL and writing user-defined functions
• Highly proficient in database technologies including RDBMS, DW/DL, Cloud, NoSQL
• Knowledge of ETL development and advanced SQL querying.
• Experience with Data profiling tools and data cleansing tools
• Experience with at least one statistical or scripting language/tool such as Python/R/SAS/SPSS
• Ability to maintain technical proficiency, work independently, multi-task
• Strong analytical problem-solving skills
• Strong verbal and written communication skills

Qualifications: BA in Information Systems with 4 years of Experience

• Experience in analytics or information technology in healthcare, including analyzing medical and pharmacy claims data, building scalable ETL processes or reporting solutions.
• Extensive experience with commercial payer data (medical and pharmacy claims, eligibility, provider data)
• Demonstrated successful experience of managing projects to drive efficiencies in data and analytic operations.
• Strong analytic skills including programming, data engineering, and scalable reporting. 
• High level of knowledge about onboarding data in various formats, ETL pipelines, automation, and data warehousing concepts.
• Generating analytic specifications and facilitating QC and UAT review
• Experience programming in Python, SQL (ETL, data manipulation, reporting), Linux environments
• Experience with Git, Bitbucket, or other version control systems
• Data warehouse and data lake environments
• Self-starter able to scope, manage, oversee and deliver end products
• Experience working with very large, diverse databases
• Deep understanding of data security procedures, HIPAA knowledge
• Experience with Value-Based Payments and population health analytics

Qualifications: BS in Statistics with 5 years of Experience

• Experience with relational databases and complex SQL
• Experience with data modeling, LookML Development
• Experience with programming languages like Python, JavaScript or Go
• Experience with Cloud Data Warehouses (AWS Redshift / Snowflake / Google Big Query)
• Experience working in an agile development framework
• Working knowledge of agile project management principles 
• Must be a team player with positive attitude and able to work with a variety of people at all levels
• Wine / Beer / Beverage industry, three-tier system, business/systems analysis and change management experience 
• Ability to work on multiple projects concurrently with shifting priorities
• Previous experience with Snowflake, Airflow (or other orchestration software), Redash and Docker.
• Previous experience with Amplitude, Salesforce, Google Analytics, Python or JavaScript
• A team player, with a positive attitude, excellent time management
• Ability to work independently with minimal supervision

Qualifications: BA in Business Analytics with 3 years of Experience