Associate Architect-Data Engineer & AI
Roles and Responsibilities
Associate Architect- Data Engineer is responsible for overseeing the design, development, and management of data infrastructure and pipelines within an organization. This role involves a mix of technical leadership, project management, and collaboration with other teams to ensure the efficient collection, storage, processing, and analysis of large datasets. The Lead Data Engineer typically manages a team of data engineers, architects, and analysts, ensuring that data workflows are scalable, reliable, and meet the business’s requirements.
Responsibilities:
● Lead the design, development, and maintenance of data pipelines and ETL processes
architect and implement scalable data solutions using Databricks and AWS.
● Optimize data storage and retrieval systems using Rockset, Clickhouse, and CrateDB.
● Develop and maintain data APIs using FastAPI.
● Orchestrate and automate data workflows using Airflow.
● Collaborate with data scientists and analysts to support their data needs.
● Ensure data quality, security, and compliance across all data systems.
● Mentor junior data engineers and promote best practices in data engineering.
● Evaluate and implement new data technologies to improve the data infrastructure.
● Participate in cross-functional projects and provide technical leadership.
● Manage and optimize data storage solutions using AWS S3, implementing best practices for data lakes and data warehouses.
● Implement and manage Databricks Unity Catalog for centralized data governance and access control across the organization.
Qualifications Required
● Bachelor's or Master's degree in Computer Science, Engineering, or related field
● 10+ years of experience in data engineering, with at least 6 years in a lead role
● Strong proficiency in Python, PySpark, and SQL
● Extensive experience with Databricks and AWS cloud services
● Hands-on experience with Airflow for workflow orchestration
● Familiarity with FastAPI for building high-performance APIs
● Experience with columnar databases like Rockset, Clickhouse, and CrateDB
● Solid understanding of data modeling, data warehousing, and ETL processes
● Experience with version control systems (e.g., Git) and CI/CD pipelines
● Excellent problem-solving skills and ability to work in a fast-paced environment
● Strong communication skills and ability to work effectively in cross-functional teams
● Knowledge of data governance, security, and compliance best practices
● Proficiency in designing and implementing data lake architectures using AWS S3
● Experience with Databricks Unity Catalog or similar data governance and metadata
management tools
Skills and Experience Required
Preferred Qualifications:
● Experience with real-time data processing and streaming technologies
● Familiarity with machine learning workflows and MLOps
● Certifications in Databricks, AWS
● Experience implementing data mesh or data fabric architectures
● Knowledge of data lineage and metadata management best practices
Tech Stack
Databricks, Python, PySpark, SQL, Airflow, FastAPI, AWS (S3, IAM, ECR, Lambda), Rockset, Clickhouse, CrateDB
Why you'll love working with us:
● Opportunity to work on business challenges from top global clientele with high impact.
● Vast opportunities for self-development, including online university access and sponsored certifications.
● Sponsored Tech Talks, industry events & seminars to foster innovation and learning.
● Generous benefits package including health insurance, retirement benefits, flexible work hours, and more.
● Supportive work environment with forums to explore passions beyond work.
●This role presents an exciting opportunity for a motivated individual to contribute to the development of cutting-edge solutions while advancing their career in a dynamic and collaborative environment.