Only USC/GC :: Lead Data Engineer jobs in United States
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Ampstek ยท 19 hours ago

Only USC/GC :: Lead Data Engineer

Ampstek is seeking a Lead Data Engineer to design, develop, and maintain scalable ETL pipelines. The role involves implementing monitoring solutions, managing deployment pipelines, and collaborating across teams to integrate analytic products with existing architecture.

IT Management
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Growth Opportunities
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Hiring Manager
David Wilfred
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Responsibilities

Design, develop, and maintain scalable ETL pipelines to ensure data quality and availability
Implement monitoring and alerting solutions to ensure data pipeline reliability and performance
Develop and manage deployment pipelines to facilitate continuous integration and delivery of data engineering solutions
Implement data integration solutions to support analytics and reporting needs
Execute the complete analytics lifecycle for problem solving, including:
Algorithm traditionalization
Model validation
Model prototyping
Data exploration
Data grooming
Survey varied data sources for analytic relevance, including:
External sources accessed via API
Flat files
Relational databases
Distributed file systems
Interpret, synthesize and communicate results of analyses to effect action and changes within the organization
Collaborate across teams to integrate analytic products with existing production architecture, develop, execute, and evaluate courses of action, and socialize results
Help teach and explain techniques and tools used to a broad set of business
Expertise in data engineering languages such as Scala (preferred) or Java, with proficiency in Python
Experience with BigData tools, particularly Spark
Proficiency in building and managing ETL pipelines
Expert-level quantitative analysis skills including interpretation of model results, consideration of causality, treatment of multicollinearity
The ability to work in compiled, high-performance languages (e.g., Scala, Java, C++)
Experience with relational databases
Strong understanding of relational databases and SQL, and familiarity with NoSQL databases
Broad experience and solid theoretical foundation on the modeling process using a
Variety of algorithmic techniques, including Machine Learning, and Graph/Network Analytics
Data pre-processing, exploratory data analysis using a variety of techniques
Basic understanding of data architecture, data warehouse, and data marts
Demonstrated ability and desire to continually expand skill set, and learn from and teach others

Qualification

ETLPythonAWSML OPSData warehousingBigData toolsSQLScalaJavaC++NoSQLGraph AnalyticsData pre-processingExploratory data analysis

Required

ETL
ML OPS
AI-ML
Data warehousing
Python
AWS
Design, develop, and maintain scalable ETL pipelines to ensure data quality and availability
Implement monitoring and alerting solutions to ensure data pipeline reliability and performance
Develop and manage deployment pipelines to facilitate continuous integration and delivery of data engineering solutions
Implement data integration solutions to support analytics and reporting needs
Execute the complete analytics lifecycle for problem solving, including: Algorithm traditionalization, Model validation, Model prototyping, Data exploration, Data grooming
Survey varied data sources for analytic relevance, including: External sources accessed via API, Flat files, Relational databases, Distributed file systems
Interpret, synthesize and communicate results of analyses to effect action and changes within the organization
Collaborate across teams to integrate analytic products with existing production architecture, develop, execute, and evaluate courses of action, and socialize results
Help teach and explain techniques and tools used to a broad set of business
Proficiency in building and managing ETL pipelines
Expert-level quantitative analysis skills including interpretation of model results, consideration of causality, treatment of multicollinearity
The ability to work in compiled, high-performance languages (e.g., Scala, Java, C++)
Experience with relational databases
Strong understanding of relational databases and SQL, and familiarity with NoSQL databases
Broad experience and solid theoretical foundation on the modeling process using a variety of algorithmic techniques, including Machine Learning, and Graph/Network Analytics
Data pre-processing, exploratory data analysis using a variety of techniques
Basic understanding of data architecture, data warehouse, and data marts
Demonstrated ability and desire to continually expand skill set, and learn from and teach others

Preferred

Expertise in data engineering languages such as Scala
Experience with BigData tools, particularly Spark

Company

Ampstek

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Ampstek supplies thousands of tech and digital professionals annually to a range of clients through its offices which spread across in 42 countries.

Funding

Current Stage
Late Stage

Leadership Team

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Rekha Pathy
CEO
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Company data provided by crunchbase