Data Engineer
Insight Global
Job Description
Laying the groundwork for data analysis and experimentation, you’ll guide clients through the digital landscape by cleaning, transforming, and aggregating data. You will be responsible for the end-to-end lifecycle of data solutions, from initial creation to production deployment. You’ll compile and install database systems, write complex queries, and implement disaster-recovery systems that scale across multiple machines.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:
Skills and Requirements
• You have a degree in computer science (or the equivalent) and a passion for big-data technologies.
• Have experience with both legacy and modernized data environments.
• At least 4 years of post-degree experience
• Hands-on experience in building end-to-end data solutions for advanced analytics.
• A firm requirement for Python proficiency, along with Java, SQL, and Scala.
• Deep knowledge of big-data technologies, specifically Hadoop and Spark.
• Required expertise in Databricks or Snowflake for data warehousing and laking.
• Familiarity with advanced-analytics tools, such as Anaconda or Spark for machine learning.
• Intellectual curiosity and the ability to work outside your comfort zone in a client-facing environment.
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