What are the responsibilities and job description for the BAULI4-Computing Architect 4 - B78-Information/Data Architecture position at ACL Digital?
Position Responsibilities:
Design, document, and maintain the Unified Data Model (UDM) artifacts and mappings.
Model process layers in the datalake, defining transformation responsibilities and lineage across layers.
Define and enforce rules for data processing, including routing tables, validation rules, enrichment logic, and error-handling policies.
Author and maintain schema definitions, attribute dictionaries, and change management processes for schema evolution.
Translate business and source system requirements into data transformation specifications to be implemented in Azure Databricks and downstream systems.
Collaborate with data engineers to design performant transformations, partitioning, and storage strategies in the datalake.
Review and approve data pipeline designs, ensuring adherence to UDM, governance, and security policies.
Work with DevOps and engineering teams to operationalize CI/CD for Databricks notebooks, jobs, and infrastructure-as-code.
Provide technical leadership and mentorship to data engineering teams, including remote collaboration with engineers located in India; coordinate design, implementation, and delivery across time zones (may require off-hour work).
Establish data quality metrics, monitoring, and remediation guidance; ensure traceability and lineage from source to consumption.
Participate in architecture and design reviews, code reviews, and agile ceremonies; drive best practices for data modeling and transformation.
Communicate architecture decisions and trade-offs to stakeholders, product owners, and engineering teams.
This position is On Site.
Describe the project/day-to-day activities they will be working on:
Designing, improving, communicating, and managing data and data models for training analytics application.
What are the Top 3-5 Technical/Software Skills needed to perform this role/job?:
Unified Data Model (UDM)
Data lakehouse concepts
Business intelligence analytical understanding
Basic Qualifications (Required Skill/Experience):
9+ years of experience in data architecture, data modeling, or related data engineering roles.
Proven experience designing and implementing Unified Data Models (UDM).
Strong expertise in Structured Query Language (SQL)
Strong expertise in data modeling across multiple process layers (raw/ingest, transformed, curated) and defining transformation logic.
Deep understanding of data governance, data lineage, metadata management, and data quality concepts.
Demonstrated experience with Databricks and building/architecting datalake solutions.
Experience defining schema evolution processes, new attribute definitions, and backward-compatible changes.
Experience authoring route tables, processing rules, and data routing/ingestion patterns.
Experience collaborating with geographically distributed engineering teams and willingness to work off hours to coordinate with teams in India.
Strong communication, documentation, and stakeholder engagement skills.
Preferred Qualifications (Desired Skills/Experience):
Prior experience in aviation, training analytics, or related operational data domains.
Experience with Azure Data Factory, Delta Lake, Unity Catalog, or equivalent data governance tools.
Familiarity with infrastructure-as-code and CI/CD practices for data pipelines (Terraform, Azure DevOps, GitOps).
Knowledge of streaming ingestion patterns, Kafka/Event Hubs, and near-real-time processing.
Experience with metadata platforms and data catalog tools (e.g., Purview, Alation).
Experience with containerization and orchestration (Docker, Kubernetes) is a plus.
Bachelor's or advanced degree in Computer Science, Information Systems, Engineering, or related field.
Design, document, and maintain the Unified Data Model (UDM) artifacts and mappings.
Model process layers in the datalake, defining transformation responsibilities and lineage across layers.
Define and enforce rules for data processing, including routing tables, validation rules, enrichment logic, and error-handling policies.
Author and maintain schema definitions, attribute dictionaries, and change management processes for schema evolution.
Translate business and source system requirements into data transformation specifications to be implemented in Azure Databricks and downstream systems.
Collaborate with data engineers to design performant transformations, partitioning, and storage strategies in the datalake.
Review and approve data pipeline designs, ensuring adherence to UDM, governance, and security policies.
Work with DevOps and engineering teams to operationalize CI/CD for Databricks notebooks, jobs, and infrastructure-as-code.
Provide technical leadership and mentorship to data engineering teams, including remote collaboration with engineers located in India; coordinate design, implementation, and delivery across time zones (may require off-hour work).
Establish data quality metrics, monitoring, and remediation guidance; ensure traceability and lineage from source to consumption.
Participate in architecture and design reviews, code reviews, and agile ceremonies; drive best practices for data modeling and transformation.
Communicate architecture decisions and trade-offs to stakeholders, product owners, and engineering teams.
This position is On Site.
Describe the project/day-to-day activities they will be working on:
Designing, improving, communicating, and managing data and data models for training analytics application.
What are the Top 3-5 Technical/Software Skills needed to perform this role/job?:
Unified Data Model (UDM)
Data lakehouse concepts
Business intelligence analytical understanding
Basic Qualifications (Required Skill/Experience):
9+ years of experience in data architecture, data modeling, or related data engineering roles.
Proven experience designing and implementing Unified Data Models (UDM).
Strong expertise in Structured Query Language (SQL)
Strong expertise in data modeling across multiple process layers (raw/ingest, transformed, curated) and defining transformation logic.
Deep understanding of data governance, data lineage, metadata management, and data quality concepts.
Demonstrated experience with Databricks and building/architecting datalake solutions.
Experience defining schema evolution processes, new attribute definitions, and backward-compatible changes.
Experience authoring route tables, processing rules, and data routing/ingestion patterns.
Experience collaborating with geographically distributed engineering teams and willingness to work off hours to coordinate with teams in India.
Strong communication, documentation, and stakeholder engagement skills.
Preferred Qualifications (Desired Skills/Experience):
Prior experience in aviation, training analytics, or related operational data domains.
Experience with Azure Data Factory, Delta Lake, Unity Catalog, or equivalent data governance tools.
Familiarity with infrastructure-as-code and CI/CD practices for data pipelines (Terraform, Azure DevOps, GitOps).
Knowledge of streaming ingestion patterns, Kafka/Event Hubs, and near-real-time processing.
Experience with metadata platforms and data catalog tools (e.g., Purview, Alation).
Experience with containerization and orchestration (Docker, Kubernetes) is a plus.
Bachelor's or advanced degree in Computer Science, Information Systems, Engineering, or related field.