Data Analytics or Analytics Engineering or Data Engineering

Intone Networks

Philadelphia, PA, United States

3 days ago

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Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

6 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Adaptable Database Systems Application Programming Interfaces (APIs) Agile Methodology Airflow Amazon Web Services Business Analytics Applications Data Analysis Microsoft Azure Bash Shell Big Data Cloud Computing Code Review

+31 more

Information Systems Continuous Integration Information Engineering Data Warehousing Debian Linux Linux DevOps Apache Hadoop Apache Hive Python (Programming Language) Performance Tuning Scrum Methodology Red Hat Enterprise Linux Power BI SQL Databases Sqoop Tableau (Software) Workflow Management Systems Software Organization Scripting Google Cloud Sql Optimization Snowflake Apache Spark Sap Business Objects Git Information Technology Data Analytics Qlikview Apache Kafka Data Pipelines

Job description

The Analytics Engineer develops and maintains scalable data models, ELT pipelines, and trusted datasets that support enterprise analytics, reporting, and self-service BI. This role partners with business stakeholders, analysts, data scientists, and engineers to deliver high-quality data products and ensure data quality, performance, and reliability., * Design and maintain dimensional data models and curated datasets.

Develop automated, scalable ELT pipelines.
Implement data quality monitoring, testing, and automation.
Partner with business users, analysts, and data scientists to deliver analytics solutions.
Support BI platforms, reporting, and dashboard migrations.
Use software development best practices including Git, code reviews, and CI/CD.
Collaborate with Data Engineering, DevOps, and Architecture teams.
Participate in Agile/Scrum ceremonies and production support.

Requirements

6+ years in Data Analytics, Analytics Engineering, BI, or Data Engineering.
Advanced SQL skills, including complex transformations and performance tuning.
Strong Data Warehousing and Dimensional Data Modeling experience.
Experience designing and maintaining Fact and Dimension tables.
Hands-on experience with Snowflake.
Experience developing analytics models using dbt.
Experience with data quality testing and validation.
Experience with Git, code reviews, and CI/CD.
Experience with BI tools such as Power BI, Tableau, Qlik, or Business Objects.
Experience with big data technologies such as Spark, Hadoop, Kafka, Hive, or Sqoop.
Experience building and consuming APIs.
Linux experience (RHEL/Debian).
Scripting experience using Python, Bash, or similar languages.
Strong analytical and problem-solving skills.
Experience working in Agile environments.

Preferred Experience

8+ years in data and analytics.
Experience with Cloud platforms (AWS, Azure, or Google Cloud Platform).
Experience with Apache Airflow or similar orchestration tools.
Experience supporting BI migrations to Power BI.
Experience with semantic models and analytics engineering best practices.
Education

Bachelor’s degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, or a related field preferred. Equivalent professional experience will be considered.

Must-Have Keywords

SQL, Snowflake, dbt, Dimensional Data Modeling, Fact Tables, Dimension Tables, Power BI