Data Architect

Job Description
Technical Skill - Data Architect, ETL, Data Engineer, Python, SQL and Any
Cloud
 
Role and Responsibilities
Develop architectural strategies for data modelling, design and implementation to meet
stated requirements for metadata management, master data management, Data warehouses,
ETL and ELT.
Analyzing business requirements, designing scalable/ robust data models, documenting
conceptual, logical & physical data model design, helping developers in development/
creating DB structures and supporting developers throughout the project life cycle.
Lead and Mentor Data Engineers: This role will be responsible for leading and
developing a team of data engineers focused on the growth in the team's skills and ability to
execute as a team using DevOps and Data Ops principles.
Investigate new technologies, data modelling methods and information management
systems to determine which ones should be incorporated onto data architectures, and
develop implementation timelines and milestones.
Recognizes and resolves conflicts between models, ensuring that information and data
models are consistent with the ecosystem model (e.g., entity names, relationships and
definitions).
Participates in the design of the information architecture: supports projects, reviews
information elements including models, glossary, flows, data usage.
Provides guidance to the team in achieving the project goals/milestones.
Works independently within broad guidelines and policies, with guidance in only the
most complex situations.
Contribute as an expert to multiple delivery teams, defining best practices, building
reusable design & components, capability building, aligning industry trends and actively
engaging with wider data communities.
 
Required Skills
Graduate or post graduate in Computer science/Electronics/Software engineering.
10+ years of relevant experience in Data modelling for DW & analytics applications /
Database related technologies.
Expert data modelling skills (i.e. conceptual, logical and physical model design,
experience with Enterprise Data Warehouses and Data Marts).
Solid understanding of cloud database technologies and services (eg..AWS, Azure ,
Redshift, Aurora, DynamoDB, Snowflake etc)
Experience in data lake technologies involving S3, Databricks Delta Lake, etc
Experience in working with data governance, data quality, and data security teams.
Experienced in knowledge-driven data processing techniques like data curation,
representation, standardization, normalization and any other type of processing that
prepares the data for integration, persistence, analysis, exchange/share and so forth.
Experience in handling very large DBs and large data volumes
Strong experience in working with and optimizing existing ETL processes and data
integration and data preparation flows and helping to move them in production.
Ability to lead and mentor teams for effective delivery
Crisp and effective executive communication skills, including significant experience
presenting cross-functionally and across all levels