Senior Data Modeler

Data Analyst Position

Not a traditional Data Analyst role. Looking for someone who has strong data modelling, relational, physical and logical data modelling concepts. Working with business to create physical model and implement Snowflake. Strong experience with creation of complex conceptual modelling. Experience with ESG Experience with Snowflake is a huge plus. Mostly remote but onsite is required when they need. Need to be local in Waltham, MA. Expect that 85 - 90% of time will be remote. Location is Waltham. Need to live in MA. Expect that they may come twice a month to an office in the first several months and then it will be twice a quarter most likely. Will be extended. Even though says this is a plus they really would love someone with experience with ESG data and data models is a plus.

A bachelor's or master's degree in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field is required. At least 10 years or more of work experience in data modeling disciplines including data integration, model optimization, and/or other areas directly relevant to data modeling responsibilities and tasks, and ideally 5 years of this experience working in cross-functional teams and collaborating with business stakeholders in utilities in support of a departmental and/or multi-departmental data management and analytics initiative. Experience with ESG data and data models is a plus. Strong experience building, managing and working with cross-functional teams in a dynamic business environment. Deep experience managing and leading teams with varied skillsets including information architects, data architects, data modelers, and data engineers. Creativity and collaboration skills Accessibility and ability to interface with, and gain the respect of, stakeholders at all levels and roles within the company. Good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.

Technical Skills Knowledge of Extensive knowledge and experience with conceptual, logical, and physical data models. Deep knowledge of 3NF and creating data models using relational design. Knowledge of NoSQL database design and dimensional design. Experience and knowledge of NoSQL databases, Snowflake is a plus. Knowledge of working with the integration of large Heterogeneous datasets: ETL/ELT Data replication/CDC Message-oriented data movement API design and access Data virtualization Streaming data Knowledge of data life cycle and data development process. Strong experience with Creation of complex conceptual, logical and physical data models using 3NF, NoSQL, and dimensional design. Hands on experience with Data modelling tools such as - ER / Studio, Erwin, PowerDesigner etc is a MUST Reviewing modifications of existing data models and systems for cross-compatibility. Implementing data strategies and data models. Updating and optimizing data and metadata models. Evaluating implemented data systems for variances, discrepancies, and efficiency. Troubleshooting and optimizing data systems. Experience with managing data modeling, architects, data analysts. Experience in Database capabilities such as: [SQL, PL/SQL, others] for relational databases NoSQL oriented databases like MongoDB, Cassandra, others] for nonrelational NoSQL databases. Analytics, and BI software tools like [Tableau, Qlik, PowerBI and others] for semantic-layer-based data discovery. Working with data science teams, helping them to refining and optimizing data science and machine learning models & algorithms, and determine metadata querying requirements. Working with the business and analytics teams to gather requirements for the data model and database design. Working with data requirements documents to design and implement the data model. It would be awesome if you had A combination of IT skills, data governance skills, and analytics. Confidence, energetic self-starter mindset, with strong interpersonal skills. Familiarity with industry standard models, preferably for the utility industry, knowledge graph networks, or ontologies. Ability to network and be recognized as a data expert across a variety of business and IT roles.