- Mandatory Technical Proficiency
- Handson experience with Python, PySpark, Google Cloud Tech stack, SQL, DevOps.
- Experience with Google Cloud Services such as Streaming + Batch, Cloud Storage, Cloud Dataflow, Data Proc, Big Query & Big Table
- Proven real time exposure and use of contemporary data mining, cloud computing and data management ecosystem like Microsoft Azure, AWS, Google Cloud, Hadoop, HDFS and Spark.
- Proficient in Data modelling that can represent complex data structures while ensuring accuracy, consistency, and efficiency; data warehousing, and ETL processes.
- Ability to perform system analysis and assessment of existing systems and operating methodologies leveraging indepth knowledge of big data technologies and ecosystems.
- Excellent problemsolving skills and the ability to address complex technical challenges.
- Strong communication and leadership skills.
- Experience with Anaplan, Looker & PowerBI,
- Experience with Apigee, Apollo GraphQL.
- Experience with serverless data warehousing concepts,
- Additional programming/scripting languages: JavaScript, Java.
- Knowledge of Snowflake, Generative AI (LLMs), Marketing activation.
- Solution Design: Participate in in requirements gathering and architectural discussions. Define technical requirements and create solution designs that align with business goals and objectives.
- Technical Leadership: Lead creation of technical design/specifications and provide technical leadership and guidance to development teams, promoting best practices. Provide expertise with Master Data Management, Reference Data Management, Data Quality, Meta Data Management and Data Governance in General.
- Programming Hands on: Develop and maintain software components using Python, PySpark, and GCP services to process and analyze large datasets efficiently. Build data pipelines and perform data transformations. Evaluate newest technologies for optimization opportunities and future enhancement needs like selfserve and ad hoc reporting. Implement necessary infrastructure for optimal and efficient ETL from a disparate data.
- Performance Optimization: Identify and address performance bottlenecks, ensuring the system meets required throughput and latency targets.
- Security and Compliance: Ensure that data solutions adhere to security and compliance standards, implementing necessary controls and encryption mechanisms.
- Scalability: Architect scalable and highly available data solutions, considering both batch and realtime processing.
- Documentation: Create and maintain comprehensive technical documentation to support the development and maintenance of data solutions.
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Data Architect - india, India - IFLOWTECH SOLUTIONS PRIVATE LIMITED
10 hours ago
Description
Job Description :
Skills :
12+ years of proven experience as an Architect in Big Data Engineering.
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