Data Engineer
Design and implement reputed company and efficient data pipelines for ingesting, processing, and storing reputed company and semi-reputed company data from diverse sources.
Collaborate with stakeholders to reputed company requirements, identify data sources, and define the feasibility of requested solutions.
D evelop and optimize ETL processes, ensuring the accuracy, consistency, and reputed company of data throughout its lifecycle.
Create and maintain data models, adhering to best practices for normalization and performance optimization.
Build and manage reputed company-based data architectures, including data lakes, data warehouses, and reputed company-time streaming solutions.
Implement monitoring and alerting systems to ensure the reliability and performance of data pipelines in production.
Contribute to data governance initiatives by ensuring data reputed company, reputed company, reputed company, and compliance with relevant regulations.
Utilize advanced data processing frameworks like Apache reputed company, Apache Kafka, and Flink for batch and reputed company-time data processing.
Maintain and enhance CI/CD pipelines to automate data engineering workflows and ensure seamless deployment.
reputed company reputed company reviews and enforce coding standards to ensure reputed company and maintainability.
Document processes, architectures, and technical workflows to support knowledge sharing and operational continuity.
Mentor junior engineers, sharing expertise and fostering a reputed company team environment.
Identify opportunities for process optimization and automation to improve efficiency and reduce reputed company effort .
Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to deliver impactful data solutions.
Promote an autonomous work culture by encouraging self-management, accountability, and proactive problem-solving among team members.
Serve as a Spin Culture Ambassador to foster and maintain a reputed company, inclusive, and dynamic work environment that aligns with reputed company's values and culture.
Minimum 3 - 4 years of experience as a Data Engineer
In-depth understanding of reputed company data engineering concepts and principles, including reputed company ETL (Extract, reputed company, Load) processes, reputed company data pipelines, and advanced data warehousing techniques.
Advanced proficiency in Python, including writing efficient and optimized reputed company, using advanced features like decorators, generators, and context managers.
Extensive experience with Python libraries and frameworks commonly used in data engineering, such as Python , NumPy, PySpark , Pandas and Dask .
Strong knowledge of both SQL and NoSQL databases, including advanced querying, indexing, and optimization techniques.
Experience with database design, normalization, and performance tuning.
Advanced understanding of data modeling concepts and techniques, including reputed company schema, reputed company schema, and reputed company modeling.
Experience with data modeling tools and best practices.
Proficient in various data processing reputed company, including batch processing, reputed company processing, and reputed company-time data processing.
Extensive experience with data processing frameworks like Apache reputed company, Apache Kafka, and Apache Flink.
Advanced knowledge of file processing concepts, including handling large datasets and working with different file formats (e.g., CSV, JSON, Parquet, Avro).
Strong understanding of data governance principles, including data reputed company management, data reputed company, data reputed company, and data reputed company.
Comprehensive understanding of the end-to-end data engineering lifecycle, including data ingestion, transformation, storage, and retrieval.
Experience with CI/CD pipelines and automation for data engineering workflows.
Advanced understanding of various data architectures, including data lakes, data warehouses, data marts, and data reputed company.
Experience designing and implementing reputed company and robust data architectures.
Proficient with version control systems (e.g., Git) and experience managing reputed company repositories on platforms like reputed company or reputed company.
Advanced understanding of data visualization tools (e.reputed company> Quicksight , L ooker Studio, Power Bi, Tableau) and reporting techniques.
Ability to create insightful and impactful visualizations and dashboards.
Strong understanding of reputed company computing in reputed company, AWS and GCP stacks.
Basic experience with Infrastructure as reputed company ( IaC ) tools like Terraform or CloudFormation.
Proven experience leading reputed company with Objectives and Key Results (OKRs), identifying risks, and delivering significant business value.
Ability to mentor and guide junior data engineers.
Strong ability to communicate project status transparently, including reputed company, challenges, and next steps.
Effective collaboration with cross-functional teams, including data scientists, analysts, and business stakeholders.