Data Architect
Realign Llc
28 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Senior Compensation
$ 162KJob location
Remote
Tech stack
Airflow
Amazon Web Services (AWS)
Azure
Google BigQuery
Databases
Data Architecture
Information Engineering
Data Governance
Data Infrastructure
ETL
Data Warehousing
Digital Architecture
Hadoop
Meta-Data Management
NoSQL
Cloud Services
SQL Databases
Google Cloud Platform
Snowflake
Data Lake
Information Technology
Data Lineage
Kafka
Data Management
Artificial Intelligence Markup Language (AIML)
Data Pipelines
Databricks
Requirements
Must Have Technical/Functional Skills
- Experience in Data Engineering, Data Management tools like Snowflake, Data Bricks, Hadoop, Kafka, Airflow, DBT
- Design Architecture for Data Lake, Data Warehouse, Lakehouse Architectures, Realtime data Platforms, ETL & ELT Pipelines, Data Governance and Quality, Data Lineage, Data Cataloging,, AI ML Data Infrastructure
Roles & Responsibilities
- Candidate should have 15+ years of IT experience with atleast 10 years in data management with Expertise in database technologies (SQL, NoSQL), data modeling tools, data warehousing concepts, ETL processes, cloud data platforms (AWS, Azure, GCP). Need strong experience in Snowflake, data bricks, Big Query and data management tools.
- Candidate should be familiar in defining and setting up data management systems for large enterprises
- Experience in Data Management tools like Snowflake, Data Bricks, Hadoop, Kafka, Airflow, DBT
- Design Architecture for Data Lake, Data Warehouse, Lakehouse Architectures, Realtime data Platforms, ETL & ELT Pipelines, Data Governance and Quality, Data Lineage, Data Cataloging,, AI ML Data Infrastructure,
- Strong analytical abilities to understand data patterns, identify data quality issues, and design solutions to address them.
- Excellent communication skills to effectively collaborate with cross-functional teams, present technical concepts to non-technical stakeholders, and gather business requirements
- Ability to troubleshoot complex data issues, identify root causes, and develop effective solutions
- Provide technical guidance and mentorship to data engineers and other data team members