Data Analyst

HomeServe USA•Norwalk, CT

14d•$82,760 - $134,868•Onsite

About The Position

The Data Analyst bridges business goals and technical solutions by gathering, documenting, and analyzing requirements. They work closely with SMEs to explore and analyze data, identify opportunities for process improvement, understand data transformation and develop data models. Strong communication, problem solving, and analytical skills are crucial for this role. The Data Analyst utilizes analytical skills, SQL, ETL/ELT and understanding data modeling and will play a key role in the deconstructions of existing Alteryx workflows and Tableau reports.

Requirements

Bachelor’s degree or equivalent experience.
Minimum of 3-5 years of experience in Data focused role.
Strong analytical, verbal and written communication and interpersonal skills.
Hands-on experience with SQL, Alteryx and Tableau reporting.
Knowledgeable with conceptual, logical and physical data models.
Familiarity with Transactional and Data Warehouse.
Well organized detail oriented with ability to work under pressure and meet deadlines while managing multiple concurrent tasks.
Competency in MS windows, MS Word, and MS Outlook.
Strong work ethic and willingness to take ownership.
Ability to work independently.
Ad-hoc responsibilities assigned.
Travel up to 10% as needed.

Responsibilities

Working closely with Business Analysts and SMEs from various business functions to understand current and future data requirements.
Using SQL to profile and analyze data from various sources, ensuring data quality by identifying gaps or inaccurate data, and how to prepare it for curation.
Responsible for deconstruction of existing Alteryx workflows and understand the transformation from the business perspective.
Assist in documentation of source to end-point data flows using MS-video and effectively communicating to stakeholders the steps of data analysis process.
Identify opportunities for improving efficiency and effectiveness, recommending solutions where appropriate.
Work with Data Engineering to review design code and test plans to increase knowledge and application of key frameworks and methodologies.
Identify relevant data attributes from internal data sources and document inputs/outputs.
Document key processes and workflows around data acquisition, integration cleansing and monitoring.
Conduct routine ad-hoc data runs and prepare write-ups in response to data queries.
Establish data validation frameworks to verify and ensure that data is accurate, consistent, and reliable.