Senior Data Architect
Dinkum SmithPune
Not disclosed
Work from Office
Full Time
Min. 1 yearJob Description
Senior Data Architect
Description
| Skill: Senior Data Architect – Data Engineering, Data Quality, Data strategy, Data on Cloud Role: T0 The ideal professional for this Data Architect role focused on data strategy and architecture will: ● Liaise with senior stakeholders to define data strategy, governance and architecture for an enterprise. ● Play a critical role in designing and architecting data engineering solutions to extract, organize, transform, consume and secure data access for authorized individuals. ● Have extensive experience with data pipeline migration and modernization. ● Be experienced in working with and extracting value from large, disconnected, and/or unstructured datasets. ● Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets. ● Create and implement data models, design databases, and ensure data security and availability. ● Hands-on experience in working with various data on cloud solutions including snowflake ● Develop and implement data quality standards and processes. ● Validate data pipelines, ETL processes, and data transformations. ● Work closely with data analysts and business users to validate data outputs. ● Establish data governance policies and procedures. ● Identify areas for continuous improvement in current systems. ● Monitor data lineage and metadata to maintain data quality over time. ● Collaborate with legal and compliance teams to address data-related legal requirements Qualifications • Bachelor's degree in information systems, a computer-related field, or equivalent professional experience (20+ years) is required. • Preferred master’s degree in management, computer science, information systems, or a related discipline, or equivalent and extensive related project experience. • Experience in multi-cloud data platform pipeline migration and hands-on experience working with AWS, Azure, or GCP. • Experience in Data & Analytics projects is a must. • Familiarity with tools like DBT, Airflow, and data test automation. • Strong skills in SQL queries in big data tools such as Hive, Impala, and Presto. • Knowledge of data profiling techniques. • Attention to detail in identifying data anomalies. • Data modeling experience – relational and dimensional with consumption requirements (reporting, dashboarding, and analytics). • Ability to apply technical knowledge to architect and design solutions that meet business and IT needs, create Data Engineering & Analytics roadmaps, drive POCs and MVPs, and ensure the long-term technical viability of new deployments, infusing key Data Engineering & Analytics technologies where applicable. • Be the Voice of the Customer to share insights and best practices, connect with the engineering team to remove key blockers, and drive migration solutions and implementations. • Demonstrated ability to build processes that support data transformation, data structures, metadata, dependency, and workload management. • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL), and working familiarity with a variety of databases. • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. • Ability to translate technical concepts to non-technical stakeholders. Skill: Senior Data Architect – Data Engineering, Data Quality, Data strategy, Data on Cloud Role: T0 The ideal professional for this Data Architect role focused on data strategy and architecture will: ● Liaise with senior stakeholders to define data strategy, governance and architecture for an enterprise. ● Play a critical role in designing and architecting data engineering solutions to extract, organize, transform, consume and secure data access for authorized individuals. ● Have extensive experience with data pipeline migration and modernization. ● Be experienced in working with and extracting value from large, disconnected, and/or unstructured datasets. ● Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets. ● Create and implement data models, design databases, and ensure data security and availability. ● Hands-on experience in working with various data on cloud solutions including snowflake ● Develop and implement data quality standards and processes. ● Validate data pipelines, ETL processes, and data transformations. ● Work closely with data analysts and business users to validate data outputs. ● Establish data governance policies and procedures. ● Identify areas for continuous improvement in current systems. ● Monitor data lineage and metadata to maintain data quality over time. ● Collaborate with legal and compliance teams to address data-related legal requirements Qualifications • Bachelor's degree in information systems, a computer-related field, or equivalent professional experience (20+ years) is required. • Preferred master’s degree in management, computer science, information systems, or a related discipline, or equivalent and extensive related project experience. • Experience in multi-cloud data platform pipeline migration and hands-on experience working with AWS, Azure, or GCP. • Experience in Data & Analytics projects is a must. • Familiarity with tools like DBT, Airflow, and data test automation. • Strong skills in SQL queries in big data tools such as Hive, Impala, and Presto. • Knowledge of data profiling techniques. • Attention to detail in identifying data anomalies. • Data modeling experience – relational and dimensional with consumption requirements (reporting, dashboarding, and analytics). • Ability to apply technical knowledge to architect and design solutions that meet business and IT needs, create Data Engineering & Analytics roadmaps, drive POCs and MVPs, and ensure the long-term technical viability of new deployments, infusing key Data Engineering & Analytics technologies where applicable. • Be the Voice of the Customer to share insights and best practices, connect with the engineering team to remove key blockers, and drive migration solutions and implementations. • Demonstrated ability to build processes that support data transformation, data structures, metadata, dependency, and workload management. • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL), and working familiarity with a variety of databases. • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. • Ability to translate technical concepts to non-technical stakeholders. |
Job role
Work locationPune
Pune
DepartmentData Science & Analytics
Role / CategoryData Science & Machine Learning
Employment typeFull Time
ShiftDay Shift
Job requirements
ExperienceMin. 1 year
About company
NameDinkum Smith
Job posted by Dinkum Smith
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