Data Architect
2 weeks ago
Data Architect
Qualifications:
12+ years of experience.
Location: Pune
Skills:
- Big data technologies and analytics: Majority of Hadoop, Hive, Cassandra, MDM, Data Lakes, Streaming data management and Analytics, Spark, Kafka, Redis, Databricks etc.
- Proficiency in programming languages such as Python, Java, Spark and associated libraries and frameworks.
- Hands-on and proficient in Databases (on-prem and Cloud), Messaging Apps, API Development and libraries.
- Very good knowledge of cloud-based architecture, APIs, frameworks for Data Engineering and Analytics.
- Knowledge of Data Governance & Data Quality Management, Metadata & Lineage Management,
- Exposure to enterprise level Data migration, Data Warehousing and DB modeling.
- Good understanding of Microservices and Test-Driven development.
- Familiarity with data visualization tools (e.g., Matplotlib, Seaborn).
- Python libraries for API development e.g. FastAPI, Flask, Django.
- Expertise standard ETL and Data Visualization tools like Talend, Tableau, Power BI etc.
- Expert in performance optimization and query tuning.
- Working knowledge on AI and ML including concepts in NLP, Computer Vision and breadth of ML algorithms, DL frameworks.
- Good knowledge of Gen AI based tools and frameworks.
Role Description:
1. Play a role of solution architect/consultant for end-to-end Data Engineering and Analytics solutions including data, technology infrastructure and models.
2. Design and development of solutions according to the business objective.
3. Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the solutions in the real world
4. Verifying data quality, and/or ensuring it via data cleaning
5. Supervising the data acquisition process if more data is needed
6. Defining data augmentation pipelines
7. Work with the technology team to plan, execute, and deliver Data Engineering Product based projects. Contribute towards the best practices regarding handling the projects.
8. Provide technical design, implementation, and support services around the creation of APIs, Models and Integration Pipelines.
9. Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools
10. Environments Understanding of the auxiliary practical concerns in production systems.
11. Strong communication, presentation and consulting skills, including technical writing skills and the ability to listen and understand client issue.
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