Data Governance Application Architect

Vista Applied Solutions Group Inc; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

A data solutions provider in Maharashtra is seeking an Integration Architect who possesses strong business acumen and experience in Data Governance. The ideal candidate will have at least 4 years of relevant experience and advanced proficiency in Python and SQL. Key tasks include managing technical platforms, enhancing data quality, and working with Agile teams. Strong knowledge in Databricks and data governance tools is essential. This position offers an opportunity to lead data management strategies within a collaborative environment.

Qualifications

• Minimum 4 years of experience with Data Governance tools.
• 3 years' experience in Python, PySpark, SQL development.
• 2 years of experience in building data quality monitoring tables.

Responsibilities

• Invest in learning latest Data Governance and Data Science solutions.
• Manage technical platforms including user access and performance.
• Coach others in SQL and Python usage.

Skills

Data Governance

Python

SQL

Databricks

Agile methodology

Tools

PowerBI

Azure Fundamentals

Databricks Unity Catalog

Job description

This is a technical role with a strong business acumen requirement; hence it is expected the Integration Architect continuously invests in learning and stays on par with the latest in Data Governance, Analytics, and Data Science approaches, solutions, frameworks, technology offerings, and best practices.

Experience:

• Minimum of 4 years of experience with Data Governance (MDM tools, data cataloging and lineage tools, data quality monitoring, and Data Governance implementations at organizations of any size).
• Minimum 3 years’ experience in Python, PySpark, SQL development.
• 2 years of experience in building data quality monitoring tables in Databricks and presenting results in PowerBI dashboards.
• Has worked with Agile development teams for at least 3 years.
• 3 years of experience in owning and managing a technical platform including but not limited to: environment management, user access management, uptime management, platform enhancements, platform updates, SaaS platform performance, etc.
• 1 to 2 years of experience in managing a small team of contractors building and maintaining system to system integrations, metadata/data extractions, and data quality rules.
• Advanced knowledge in writing SQL and Python with a demonstrated ability to coach others.
• 2 years of experience managing large data quality rule environments using Databricks Unity Catalog.
• Strong understanding of Databricks LakeFlow integration preferred.
• 2 years of experience building reference architecture diagrams and managing implementation.
• 4 years of experience managing Master Data Management platforms including match/merge crosswalk logic, large scale data models with multiple sources of truth, and managing downstream consumption.
• Understanding of technical privacy policy enforcement through automation preferred.
• Certifications: Azure Fundamentals, Azure Data Fundamentals, Databricks, Data Governance are considered a plus.

Preferred Skills:

• Data visualization in any BI tool or code library.
• Experience defining, creating, delivering, and maintaining data and analytics solutions in the cloud.
• Advanced knowledge in Databricks Unity Catalog management and Data Governance
• Working knowledge of modern enterprise systems such as Enterprise Resource Planning (SAP), Marketing and Sales Clouds (Salesforce), MDM systems, metadata management platforms, and enterprise analytics/reporting environments (SSRS, Azure Synapse).
• Advanced Data Analysis in Databricks, Excel, SQL, Python, R, or any combination of these.
• Understanding of modern data ecosystems, data management, data governance, and data products (cloud data warehousing, analytics in the cloud, AI/ML solutions).
• Owning a data domain portfolio including but not limited to: building and maintaining data management strategy/implementation, managing relationships and expectations with data domain stakeholders and owners, managing assigned resources using an agile methodology, and delivering value driven results that executive leadership can understand.