GCP Data Engineer

About the opportunity

Description GCP Data Engineer Remote, US $75-85k plus bonus plus benefits For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process. Cloud Data Engineer – Job description The Cloud Data Engineer is a hands-on role responsible for performance, availability and scalability of the public cloud environment. You will collaborate with other Architects and Engineers to enable enterprise applications to meet the organizations business goals. Responsibilities Role and Responsibilities: Work closely with application development and data engineers on day-to-day tasks. Participate in project planning and implementation. Coordinate with Data Scientists, Product Managers and business leaders to understand data needs and deliver on those needs. Create and maintain optimal data pipeline architecture. Assemble large, complex data sets that meet functional / non-functional business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and other data sources. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. Improve, optimize and identify opportunities for efficient software development processes. Help achieve milestones as per sprint plan and prioritize to manage ad-hoc requests in parallel with ongoing sprints. Qualifications Required Qualifications: 5+ years of hands-on experience in building Data pipeline (ETL/ELT) in a cloud platform GCP knowledge strongly preferred - other cloud experience such as AWS. AZURE is ok 5+ years of hands-on experience of building and operationalizing data processing systems Strong Python scripting experience is very important requirement 2+ years’ experience in NoSQL databases and close familiarity with technologies/languages such as Python/R, Scala, Java, Hive, Spark, Kafka 2+ years’ experience working with data platforms (Data warehouse, Data Lake, ODS) 2+ years’ experience working with tools to automate CI/CD pipelines (e.g., Jenkins, GIT, Control-M) Must have working experience with the clinical data GCP (google cloud platform) experience 3+ years of experience working on healthcare / clinical data Preferred Qualifications: Data analysis / Data mapping skills Python Cloud Data flow/Data proc/Function Whistle map SDK Google Health care API/ FHIR store What we offer: EXL Analytics offers an exciting, fast paced and innovative environment, which brings together a group of sharp and entrepreneurial professionals who are eager to influence business decisions. From your very first day, you get an opportunity to work closely with highly experienced, world class analytics consultants. You can expect to learn many aspects of businesses that our clients engage in. You will also learn effective teamwork and time-management skills - key aspects for personal and professional growth Analytics requires different skill sets at different levels within the organization. At EXL Analytics, we invest heavily in training you in all aspects of analytics as well as in leading analytical tools and techniques. We provide guidance/ coaching to every employee through our mentoring program wherein every junior level employee is assigned a senior level professional as advisors. Sky is the limit for our team members. The unique experiences gathered at EXL Analytics sets the stage for further growth and development in our company and beyond.

Responsibilities

• The top of the range is reserved for candidates who notably exceed the
• : Work closely with application development and data engineers on day-to-day tasks.
• Participate in project planning and implementation.
• Coordinate with Data Scientists, Product Managers and business leaders to understand data needs and deliver on those needs.
• Create and maintain optimal data pipeline architecture.
• Assemble large, complex data sets that meet functional / non-functional business

Qualifications

• ; the lower end applies to those with less experience or fewer
• For positions based in higher-cost zones (e.
• , California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.
• Cloud Data Engineer – Job description The Cloud Data Engineer is a hands-on role responsible for performance, availability and scalability of the public cloud environment.
• You will collaborate with other Architects and Engineers to enable enterprise applications to meet the organizations business goals.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and other data sources.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.