Sr. Data Architect

Must have - The candidate must have experience in data warehouse models in addition to OLTP models. These models will be architected at the following layers: conceptual, logical, physical, subject area, and application.

Title: Sr. Data Architect

Location 135 Santilli Highway Everett MA 02149

Start: ASAP

Duration: 1 year W/probable extensions

Interview Process: 1 Tech phone screens 1 Skype or face to face if local.

Hours / Shift: Monday –Friday 9:00 to 5:00

Notes: . 40 hours Hybrid Role –

Responsibilities: 1. The candidate must have experience in data warehouse models in addition to OLTP models. These models will be architected at the following layers: conceptual, logical, physical, subject area, and application.

• Work collaboratively on design implementation with other architects, ensuring that key requirements are preserved, and potential gaps are understood and communicated to stakeholders as appropriate.
• Ensure design governance across projects, applications, and infrastructure.
• Create short-term tactical solutions to achieve long-term objectives and an overall data management roadmap.
• Establish processes for governing the identification, collection, and use of corporate metadata; take steps to assure metadata accuracy and validity.
• Establish methods and procedures for tracking data quality, completeness, redundancy, and improvement.
• Ensure that data strategies and architectures are in regulatory compliance.
• Oversee the mapping of data sources, data movement, interfaces, and analytics, with the goal of ensuring data quality.
• Address data-related problems regarding systems integration, compatibility, and multiple platform integration.
• Develop and implement key components as needed to create testing criteria that will guarantee the fidelity and performance of data architecture.
• Document the data architecture and environment to maintain a current and accurate view of the larger data picture.
• Identify and develop opportunities for data reuse, migration, or retirement.
• Analyze and mine business data to identify patterns and correlations among the various data points.
• Develop and promote data management methodologies and standards.
• Develop integration process data flows and data mapping analyses.
• Maintain code in GitHub, ensuring proper version control and adherence to coding standards.
• Accurately and promptly log all work, including estimates and time spent, in JIRA.
  
  

Required Qualifications

• 4-7 years overall experience in Data Integration, Data Architecture, Data Modeling, and implementation.
• 4-7 years of full lifecycle data warehousing experience.
• In depth hands-on experience designing, implementing, and troubleshooting ETL/ELT processes.
• Knowledge of relational database designs and concepts including normalization and dimensional models.
• Knowledge of state longitudinal data systems and preparing them for technological advancements and features.
• Experience with Apache Airflow and creating DAGs to move data from source to target.
• Experience with Python coding.
• Develop system/integration test plans and scenarios for data loads and extracts.
• Manage and monitor production and non-production ETL sessions.
• Ability to coordinate and work with network and other system administration teams to isolate resource bottlenecks (bandwidth/network, CPU, memory, disk/storage).
• Good knowledge of applicable data privacy practices and laws (FERPA).
• Knowledge of different standards in the Education domain CEDS, ED-FI, SIF.
• Familiarity with student academic performance data and education data concepts.
• BI knowledge: 3-5 years in BI from ETL perspective.
• Ability to observe steps and ascertain success of step or failure and root cause of step(s).
• Direct experience in implementing enterprise data management processes, procedures, and decision support.
• Experience in Dimensional Modeling.
• Experience with Snowflake a plus.
• Experience with modern data management in the cloud, preferably AWS (e.g., RDS,