[Remote] Analytics Engineer II
Note: The job is a remote job and is open to candidates in USA. eTeam is recruiting for a contract Analytics Engineer II role focused on transforming raw data into curated, trusted data sets that support enterprise analytics and self-service reporting. The position develops scalable ELT pipelines and data models, maintains data quality, supports analytics and data science teams, and partners across business units to deliver data products for data-driven decision-making.
Responsibilities
- Collaborate with business subject matter experts, data analysts, and data scientists to understand/identify the opportunities to develop well-defined, integrated, re-usable data sets which power analytics
- Codify reusable data access patterns to speed up time to insights
- Perform Logical and Physical data modeling with an agile mindset
- Build automated, scalable, test-driven ELT pipelines
- Utilize software development practices such as version control via Git, CI/CD, and release Management
- Build data products using various visualization, BI tools and data science tools
- Collaborate with Data Engineers, DevOps engineers and architects on improvement opportunities for DataOps tools and frameworks
- Implement data quality frameworks and data quality checks
- Help define analytical product roadmap to drive the business goals and superior quality outcomes
- Work with Data Scientists, Statisticians and Machine learning engineers to implement/scale advanced algorithms to solve health care, operational and quality challenges
- Work independently and effectively manage ones time across multiple priorities and projects
- Make recommendations about platform adoption, including technology integrations, application servers, libraries, and frameworks
- Participate in a shared production on-call support model
- Be a critical part of a scrum team in an agile environment, ensuring the team successfully meets its deliverables each sprint
Skills
- Minimum of six (6) years of experience working in data and analytics landscape
- Strong SQL, Data Modeling and Data Warehousing fundamentals
- Experience with software development practices; version control, code review, CI/CD
- Experience with data integration tools: DBT, Informatica, MS Integration Services etc
- Experience with big data toolset: Hadoop, Spark, Kafka, Hive, sqoop etc
- Experience working with Business Intelligence Tools (Business Objects) or Visualization tools such as Qlik, Tableau, PowerBI etc
- Experience with stream-processing systems: IBM Streams, Flume, Storm, Spark-Streaming, etc
- Good hands-on experience with Linux (RHEL/Debian) operating system
- Ability to code with other scripting languages such as Python, Bash, groovy etc
- Experience consuming and building APIs
- Experience utilizing Agile methodology for development
- Bachelor's degree in Computer Science, Computer/Software Engineering, Information Technology or related fields
- Experience with workflow orchestration tools such as Apache Airflow for scheduling and managing analytics and data transformation pipelines
- Experience using Python for data transformation, validation, or analytics workflows (nice to have)
- Minimum of eight (8) years of experience working in data and analytics landscape
- One (1) year of experience working with at least one of the public cloud platforms such AWS/Azure/GCP
- Advanced SQL for analytics engineering, including complex transformations, aggregations, and performance tuning
- Strong dimensional data modeling skills, including design and implementation of fact and dimension tables
- Hands-on experience with Snowflake as a cloud data warehouse for analytics workloads
- Experience developing and maintaining analytics models using dbt, including testing and documentation
- Proven ability to refactor existing analytical data models to support reporting and dashboard migrations
- Experience supporting enterprise BI platforms, preferably Power BI, including semantic model alignment
- Strong analytical and problem-solving skills, with the ability to evaluate tradeoffs and recommend optimal modeling approaches
- Experience with Apache Airflow or similar workflow orchestration tools for scheduling and managing analytics pipelines
- Experience using Python for data transformation, validation, automation, or analytics workflows
- Familiarity with Agile or iterative delivery practices
- Experience with version control and modern analytics development practices (e.g., Git, pull requests, code reviews)
- Experience supporting BI platform migrations (e.g., Qlik, Business Objects, or similar to Power BI)
- Advanced degree in Computer Science, Informatics, Information Systems or another quantitative field
- Candidates with equivalent practical experience in analytics engineering, data modeling, or BI development are strongly encouraged to apply
- Relevant professional experience, demonstrated technical capability, and a track record of delivering analytics solutions will be weighted more heavily than formal education or certifications
- A Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, or a related field is helpful but not required
Benefits
- Hybrid work model
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