Amazon Web Services (AWS), Analysis Skills, Apache Hadoop, Apache Spark, Big Data, Business Strategy, Cloud Computing, Communication Skills, Cross-Functional, Data Collection, Data Management, Data Modeling, Data Quality, Data Sets, Data Storage, Data Warehousing, Database Extract Transform and Load (ETL), Experiment Design, Manufacturing/Industrial Processes, Needs Assessment, Problem Solving Skills, Python Programming/Scripting Language, Reporting Dashboards, SQL (Structured Query Language), Scala Programming Language, Scalable System Development, Testing
Primary & Secondary Skill SQL/Python/Data Engineer/AWS
Data Engineers who can build scalable, reliable data pipelines and infrastructure, requiring mastery in SQL, Python/Scala, cloud platforms (AWS), and big data technologies (Spark, Kafka, Hadoop).
Key skills include data modeling, ETL/ELT pipeline construction, data warehousing and orchestration tools like Airflow.
Strong problem-solving, collaboration, and data governance skills are crucial. Collect, process, and analyze large datasets to extract meaningful insights.
Design and conduct experiments to test hypotheses and validate data-driven solutions.
Collaborate with cross-functional teams to identify data needs and align strategies with organizational goals.
Create templates, dashboards and visualizations to communicate findings effectively to stakeholders.
Ensure data integrity and accuracy through cleaning, preprocessing, and validation techniques.
Optimize data collection and storage processes for efficiency and scalability. Knowledge on Manufacturing process is preferred