Data Architect - Python/SQL/ETL
Growel Softech Pvt. Ltd.
Key Responsibilities : - Design and implement scalable, high-performance enterprise data architectures.- Define data models, data flows, integration patterns, and architecture standards.- Develop and review Python-based data engineering solutions, frameworks, and reusable components.- Design and optimize ETL/ELT pipelines for large-scale data processing.- Work with structured and unstructured data across data lakes, data warehouses, and modern data platforms.- Define strategies for data ingestion, transformation, storage, processing, and consumption.- Collaborate with data engineers, software engineers, BI teams, and business stakeholders.- Evaluate existing data platforms and recommend improvements for scalability, performance, reliability, and cost optimization.- Establish data architecture best practices, standards, governance, and security principles.- Perform technical reviews and provide architectural guidance to development teams.- Troubleshoot complex data pipeline, integration, and performance issues.- Support cloud migration and modernization initiatives.- Create architecture diagrams, technical documentation, and solution design documents.- Mentor data engineering teams and provide technical leadership on complex projects.Required Skills & Experience : - 8+ years of experience in data engineering, data architecture, or a related technology role.- Excellent understanding of data structures, algorithms, object-oriented programming, and Python frameworks/libraries.- Strong experience designing ETL/ELT pipelines and data integration solutions.- Expertise in data modeling, including conceptual, logical, and physical data models.- Experience with relational and NoSQL databases such as : a. PostgreSQLb. SQL Serverc. MySQLd. MongoDB- Other enterprise database technologies- Strong SQL skills and experience with query optimization and performance tuning.- Experience with modern data warehouse and data lake architectures.- Hands-on experience with cloud data platforms such as AWS, Azure, or GCP.- Experience with distributed data processing technologies such as Apache Spark/PySpark is preferred.- Experience with orchestration and workflow tools such as Apache Airflow, Azure Data Factory, AWS Glue, or equivalent.- Knowledge of data governance, data quality, security, metadata management, and data lineage.- Experience designing scalable and highly available data solutions. (ref:hirist.tech)
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