Senior AI / Data Science Engineer – Data Engineering

Job Description:

A Day in the Life

• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and translate them into efficient and scalable data solutions.
• Design and develop end-to-end data pipelines encompassing data ingestion, transformation, storage, and delivery.
• Utilize strong programming skills in Python to write clean, maintainable, and optimized code for data processing tasks.
• Leverage expertise in Apache Spark and PySpark to distribute data processing across clusters and handle large datasets efficiently.
• Possess a deep understanding of SQL (Oracle/SQL Server) and NoSQL databases (Big Data) to manage and query data effectively at scale.
• Design and implement data pipelines on cloud platforms like AWS, Azure, or Snowflake for scalability and cost-effectiveness, leveraging services like S3, Blob Storage, or Data Lake Storage.
• Orchestrate data pipelines using tools like Airflow or similar solutions to ensure smooth data flow, automation, and reliable scheduling.
• Build and maintain integrations with RESTful and SOAP web services to facilitate seamless data exchange between systems.
• Monitor and troubleshoot data pipelines to ensure data quality, consistency, and timely delivery.
• Champion best practices for data engineering and maintain a high standard of code documentation.
• Stay up-to-date on the latest advancements in data engineering tools and technologies, including Big Data frameworks and cloud platforms.

Must Have

Job Responsibilities

• 8+ & 14+ years of experience in data engineering with a proven track record of designing and implementing data pipelines.
• Strong programming skills in Python with proficiency in libraries like Pandas, Spark, and PySpark for data manipulation and analysis.
• In-depth knowledge of SQL (Oracle/SQL Server) and NoSQL databases (Big Data) for data storage and retrieval at scale.
• Experience with data pipeline orchestration tools like Airflow or similar solutions.
• Experience designing and implementing end-to-end data solutions, from data ingestion to consumption.
• Familiarity with cloud platforms (AWS, Azure, Snowflake) for data storage, processing, and services.
• Understanding of web service protocols (REST, SOAP) and experience building data integrations.
• Excellent problem-solving and analytical skills with a passion for building efficient data infrastructures.
• Effective communication and collaboration skills to work effectively with cross-functional teams.

Minimum Qualification

• Bachelors / Master’s of Engineering in Computer Science, Statistics, Mathematics, or a related technical field (PhD is a plus).
• 8+  & 14+ years of Software industry experience.

Principal Working Relationship

• Reports to the AI / Data Science Manager.
• Collaborates with data scientists, business analysts, data analysts, and other data engineers.

Nice to Haves

• Experience with real-time data processing frameworks (Apache Kafka, Apache Flink).
• Experience with data governance and data security best practices.
• Experience with data visualization tools (Tableau, Power BI) for data exploration.
• Experience with DevOps practices for continuous integration and deployment (CI/CD) of data pipelines.