Data Architect

Responsibilities: •Design, implement, and maintain robust ETL/ELT processes to ingest, clean, and transform data from multiple sources •Process and manage complex datasets to support business and analytical needs •Conduct regular testing and enhancement of data pipelines to improve efficiency •Implement best practices for data validation, testing, and monitoring, proactively identifying and resolving issues to maintain data integrity •Collaborate with software engineers and AI/ ML engineers to ensure seamless data accessibility •Implement best practices for data governance, security, and quality assurance •Document data architectures, lineage, and metadata to ensure transparency and reproducibility Qualifications: •5+ years of experience in data engineering, ETL development, or data warehousing •Demonstrated ability to design and manage ETL/ELT processes using tools like Airflow, Luigi, or dbt to automate data workflows and transformations •Experience with big data architectures and optimizing data pipelines •Deep familiarity with SQL for data manipulation and querying •Strong coding skills in Python, and at least one other language (Scala/Java) •Hands-on experience with cloud-based data platforms (Azure/AWS/GCP) •Strong analytical skills for working with large-scale unstructured datasets •Ability to diagnose data issues, optimize performance, and communicate technical solutions effectively to both technical and non-technical stakeholders •Educational qualifications: Bachelor’s degree in Computer Science, Engineering, or related field required

5+ years of experience in data engineering, ETL development, or data warehousing. Experience designing and managing ETL/ELT processes using tools like Airflow, Luigi, or dbt. Experience with big data architectures and optimizing data pipelines. Deep familiarity with SQL. Strong coding skills in Python, and at least one other language (Scala/Java). Hands-on experience with cloud-based data platforms (Azure/AWS/GCP). Strong analytical skills for working with large-scale unstructured datasets. Ability to diagnose data issues, optimize performance, and communicate technical solutions to both technical and non-technical stakeholders. Bachelor’s degree in Computer Science, Engineering, or related field.

Design, implement, and maintain robust ETL/ELT processes to ingest, clean, and transform data from multiple sources. Process and manage complex datasets to support business and analytical needs. Conduct regular testing and enhancement of data pipelines to improve efficiency. Implement best practices for data validation, testing, and monitoring, proactively identifying and resolving issues to maintain data integrity. Collaborate with software engineers and AI/ML engineers to ensure seamless data accessibility. Implement best practices for data governance, security, and quality assurance. Document data architectures, lineage, and metadata to ensure transparency and reproducibility.