Hands on experience in Spark, Python/Scala, Azure Databricks, Data Pipelines, SQL Server / NoSQL.
Strong working knowledge in Python, Scala, SQL, Airflow and PySpark.
We are looking for a Senior Data Engineer with strong expertise in Apache Spark, Python, and Azure Databricks to design and implement scalable data pipelines.
The ideal candidate will have hands-on experience in building ETL workflows, optimizing Spark jobs, and working with cloud-based data platforms on Azure.
6+ years of experience building data pipelines
6+ years of experience building data frameworks for unit testing, data lineage tracking, and automation.
Fluency in any programming language Python is required.
Working knowledge of Apache Spark.
Familiarity with streaming technologies (e.g., Kafka, Kinesis, Flink).
Excellent communication and collaboration skills.
RESPONSIBILITIES:
Writing and reviewing great quality code
Understanding the clients business use cases and technical requirements and be able to convert them in to technical design which elegantly meets the requirements
Mapping decisions with requirements and be able to translate the same to developers
Identifying different solutions and being able to narrow down the best option that meets the clients requirements
Defining guidelines and benchmarks for NFR considerations during project implementation
Writing and reviewing design documents explaining overall architecture, framework, and high-level design of the application for the developers
Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed
Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it
Understanding and relating technology integration scenarios and applying these learnings in projects
Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken
Carrying out POCs to make sure that suggested design/technologies meet the requirements.
