Full-Time Senior Big Data Engineer

Requirements:

• 10+ years of experience.
• Strong knowledge and experience in Big data engineering.
• Expertise in Databricks and Python.
• Strong experience with architecture and development in Azure cloud services such as ADF, ADLS, Azure SQL, Logic Apps, and Azure Functions.
• Hands-on experience in Databricks and related architecture like Medallion.
• Experience in implementing and delivering data solutions and pipelines on Databricks.
• A strong understanding of data modeling, data structures, data warehouses, databases, and ETL processes.
• Expert in software development activities like code maintainability, deployment, unit testing, etc.
• An in-depth understanding of large-scale data sets, including structured and unstructured data.
• Hands-on experience in SQL.
• A basic understanding of CI/CD and DevOps.
• Experience with building and maintaining a cloud system.
• Familiarity with data modeling, data warehousing, and building distributed systems.
• Expertise in Spanner for high-availability, scalable database solutions.
• Knowledge of data governance and security practices in cloud-based environments.
• A problem-solving mindset with the ability to tackle complex data engineering challenges.
• Strong communication and teamwork skills, with the ability to mentor and collaborate effectively.
• Bachelor's or master's degree in computer science, Information Technology, or a related field.

Responsibilities:

• Writing and reviewing great quality code.
• Understanding the client’s business use cases and technical requirements and convert them into technical design.
• Mapping decisions with requirements and translate them to developers.
• Identifying different solutions and narrowing down the best option.
• Defining guidelines and benchmarks for NFR considerations.
• Writing and reviewing design documents explaining architecture, framework, and high-level design.
• Reviewing architecture and design on various aspects.
• Developing and designing the overall solution.
• Understanding and applying technology integration scenarios.
• Resolving issues through root cause analysis.
• Carrying out Proof of Concepts (POCs).

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