Senior Data Engineer - Cloud and Business Intelligence
OnJob Demo
Noida ,Uttar Pradesh , India 
₹ 14 - ₹ 21 /Yr 
2 - 5
Yrs
Skills
Job Description
1. Overview:
The Senior Data Engineer - Cloud and Business Intelligence will play a crucial role in designing, developing, and maintaining our company's data infrastructure and business intelligence solutions. This individual will be responsible for architecting and implementing robust, scalable, and secure data pipelines, transforming raw data into actionable insights for business decision-making. The primary objective is to enhance data accessibility, improve data quality, and empower stakeholders with data-driven insights.
2. Key Responsibilities:
Design, develop, and maintain efficient and scalable data pipelines using cloud-based technologies.
Develop and implement data warehousing solutions on cloud platforms (AWS, Azure, GCP).
Build and optimize ETL/ELT processes for various data sources.
Design and implement data models optimized for performance and query efficiency.
Develop and maintain data quality processes and monitoring systems.
Collaborate with business stakeholders to understand their data needs and translate them into technical solutions.
Create and maintain documentation for data pipelines, data models, and data governance processes.
Proactively identify and resolve data-related issues.
Participate in the design and implementation of cloud-based data security and governance strategies.
Mentor and guide junior data engineers.
3. Technical Skills:
Expertise in cloud computing platforms (AWS, Azure, GCP) – demonstrated experience with at least two.
Strong experience with data warehousing principles and technologies (Redshift, Synapse Analytics, BigQuery).
Proficiency in ETL/ELT tools and techniques (AWS Glue, Azure Data Factory, Dataflow).
Advanced proficiency in SQL and at least one scripting language (Python preferred).
Experience with data streaming technologies (Pub/Sub, Kafka).
Experience with data visualization tools (Power BI strongly preferred).
Familiarity with data modeling techniques (star schema, snowflake schema).
Experience with Row-Level Security (RLS) implementation.
Experience with data lake and data warehouse architectures.
Experience with serverless computing (Lambda, Azure Functions).
Advanced DAX expertise for Power BI development.
Experience with machine learning platforms (Azure ML a plus).
Experience with S3 (AWS) or similar cloud storage services.
4. Required Qualifications:
Bachelor's degree in Computer Science, Engineering, or a related field.
5+ years of experience as a Data Engineer.
Proven experience in designing and implementing cloud-based data solutions.
Strong analytical and problem-solving skills.
Excellent communication and collaboration skills.
5. Skills & Experience:
This role requires a strong foundation in the following areas, with demonstrable experience:
Power BI: Advanced skills in report creation, data modeling, and DAX development. Experience creating interactive dashboards and visualizations.
Cloud: Deep understanding of cloud architectures, principles, and best practices.
Google Cloud Platform (GCP): Experience with BigQuery, Dataflow, Pub/Sub.
Microsoft Azure: Experience with Azure Data Factory, Synapse Analytics, Azure ML.
AWS: Experience with AWS Glue, Lambda, S3, Redshift.
Advanced DAX: Proven ability to write complex DAX formulas for performance optimization and advanced calculations.
Data modeling and optimization: Expertise in designing efficient and scalable data models.
Row-Level Security: Implementing RLS for data security and access control.
AWS Glue, Lambda, S3: Hands-on experience with these AWS services for data processing and storage.
Redshift, Azure Data Factory, Synapse Analytics, BigQuery, Dataflow, Pub/Sub: Demonstrable experience using these technologies for data integration and warehousing.
Data warehouse: Solid understanding of data warehouse design principles and implementation.
Azure ML: Experience with Azure Machine Learning services is a plus.
