A client of Insight Global has an excellent opportunity for aData Solutions Engineering & Analytics Manager to join our Digital Transformation Team inMarietta, GA
In this position you will be a leader in driving the business vision, prioritization, and execution of data initiatives as part of the client’s Digital Transformation. Will be responsible for developing the data platform that will be able to take the digital data collected from the various resources and be able to help the BU”s to develop successful strategic business programs.
What you’ll be doing:
* SME in development of the platform to unify all the data across the enterprise as well as other external data sources and advance the vision for digital transformation and innovation at the client.
* Responsible for data platform vision and strategy — create a clear, convincing technical strategy that aligns to business priorities and objectives.
* Responsible for developing data products from proof of concept to scalable solutions based on business priorities and impact, using modern tools and technologies on the cloud.
* Utilize Artificial Intelligence (AI)/Machine Learning (ML) to elevate our organization towards more advanced analytics.
* Guide the development of data structures and pipelines that organize, collect, and standardize data to generate insights and address reporting needs.
* Optimize the data pipeline platform to support scalable workloads and diverse use cases.
* Define and deploy data architecture and enable top-down governance models.
* Lead an enterprise culture shift towards a data-driven culture.
* Increase adoption of data & analytics (D&A) via self-service and data catalog.
* Enable data driven business decisions for a wide population of business users by providing advanced access to data & analytics information via easy combinations of elements.
* Decision Marking:
o The position will be accountable for all the DX Data product engineering decisions (Strategy, Features, Releases, etc.) and the management of the data budget.
Required Skills & Experience
* Bachelor’s Degree or equivalent in Computer Sciences, Data Analytics, Management Information Systems, or related quantitative field in Data Engineering
* 8+ years of experience in designing and building new scalable on-prem/cloud data engineering solutions using distributed frameworks like Spark, Hadoop etc.
* Experience building and leveraging Customer Data Platforms such as Treasure Data to enable personalization and customer segmentation.
* Coding: Strong hands-on experience with languages like Python, PySpark, SQL, UNIX/Linux scripting to access, extract, manipulate and summarize data.
* Data Engineering: Experience in core data engineering activities like:
o Database optimization (partitioning, group and sort keys, indexes, query optimization),
o Data processing: (Spark, SQL Server, PostgreSql, Hadoop/Hive),
o Programming and/or scripting experience: (Python, PySpark, Bash),
o Data cleansing, Integration testing (PyTest or Unittest)
* Automation: Experience in automation and testing of data workflows, preferably Apache Airflow
* Familiarity with a broad base of analytical methods like Data modeling, variable based transformation & summarization, and algorithmic development.
* Experience working with: Airflow, Kubernetes, Cloud infrastructure (e.g., Azure, GCP), CI/CD (e.g., Azure DevOps, Git actions, Jenkins, or CircleCI)
* Hands-on experience with cloud data warehousing services like Snowflake and/or Big Query.
* Experience in SnowSQL, GCP – BigQuery, Cloud SQL, DataFlow, Pub/Sub, Cloud Functions etc.
* Experience in Google Analytics 4 (GA4) is a must.
* Experience with owning or overseeing ML Ops processes like Continuous Integration (CI), Continuous Delivery (CD), Continuous Training (CT), and Continuous Monitoring (CM) is a plus.
* Understanding of upcoming data technology trends like The Data Fabric from conceptualization to implementation.