Senior Data Engineer - I

AI in this role

Design and optimize data pipelines, ETL processes, and big data infrastructure for large-scale enterprise analytics.

sqlawsaws-redshifthadoopairflowaws-glueamazon-s3aws-emrkafkakinesis

etlbig-datadata-engineeringdata-pipelinestreamingalgorithms

Job Title

Senior Data Engineer - I

Job Description

Your role:

• Build the infrastructure required for extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies

• Develop, maintain and optimize ETLs to increase data accuracy, data stability, data availability and pipeline performance

• Strong knowledge in the Big data tools such as AWS Redshift, Hadoop, map reduce etc.

• Having knowledge in tools like Airflow, AWS Glue, S3, AWS EMR, Streaming data pipelines, Kafka/Kinesis is desirable

• Assists in solving data engineering challenges by analyzing data issues and applying simple solutions, working under general supervision.

• Helps develop technical solutions by integrating data from different sources and conducting basic feasibility checks.
• Supports complex data requests and queries by ensuring detailed and accurate responses that align with business needs and advanced technical capabilities, providing guidance and insights.
• Ensures data accuracy in reports by following validation and verification protocols, maintaining exemplary data quality standards, and ensuring compliance with industry regulations.
• Develops and optimizes algorithms to transform raw data into detailed statistical analyses to drive informed decision-making and enhance business operations.
• Automates the generation of advanced data analysis charts and graphs, enhancing reporting processes' efficiency and improving data visualizations' clarity and utility.
• Extracts detailed information on specific data sets quickly and efficiently, providing comprehensive analyses that support critical business operations and decision-making processes.
• Responds promptly to queries from various business units, offering expert guidance on data trends and providing in-depth insights on product or trend-specific concerns.
• Suggests improvements by evaluating existing tools, systems, and databases, identifying opportunities for enhancements, and recommending solutions to drive innovation.
• Documents statistical-based trending procedures and validates analysis processes in strict compliance with regulatory requirements, ensuring transparency, adherence to industry standards.

Minimum required Education:
Bachelor's / Master's Degree in Computer Science, Information Management, Data Science, Econometrics, Artificial Intelligence, Applied Mathematics, Statistics or equivalent.

Minimum required Experience:
Minimum 10 years of experience with Bachelor's in areas such as Data Handling, Data Analytics, AI Modeling or equivalent OR no prior experience required with Master's Degree.

How we work together
We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.

About Philips
We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.
• Learn more about our business.
• Discover our rich and exciting history.
• Learn more about our purpose.
If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our culture of impact with care here.

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How we rate this

Senior Data Engineer - I at Philips rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ETLBig DataData EngineeringData PipelineStreamingAlgorithmsSQLAWS

Questions you could be asked

Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where big data was part of your work. What did you do?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where data pipeline was part of your work. What did you do?
Tell me about a project where streaming was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: ETL, Big Data, Data Engineering, Data Pipeline, and Streaming. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.

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