Data Engineer IV (6329)

itD Tech

23h•Remote

About The Position

itD is seeking a Data Engineer IV to design and scale data infrastructure that powers customer experience insights across Company Post Sales Organization. This role will drive the development of robust data pipelines, enable AI-driven analytics, and deliver high-impact data solutions that enhance customer support, operations, and business decision-making. The ideal candidate will bring deep expertise in data engineering and AI enablement and a proven track record of delivering scalable data pipelines, self-service analytics platforms, and automation solutions.

Requirements

6+ years of experience in data engineering, analytics, or related domain
Strong proficiency in SQL (complex queries, performance tuning) and Python
Experience designing and building production-grade ETL/ELT pipelines at scale
Hands-on experience with workflow orchestration tools (e.g., Airflow or equivalent)
Experience with data warehousing platforms (e.g., Spark, Hive, Snowflake, BigQuery)
Experience building data visualizations and dashboards (Tableau or similar tools)
Strong understanding of data modeling and data governance best practices
Experience enabling AI/ML workflows, including feature pipelines or AI-assisted analytics

Nice To Haves

Experience with generative AI tools, prompt engineering, or LLM-based workflows
Familiarity with streaming data technologies (e.g., Kafka, Spark Streaming)
Experience with CI/CD, version control (Git), and infrastructure-as-code practices
Background in customer experience or customer support operations analytics
Experience with digital analytics tools (e.g., Google Analytics, Adobe Analytics)
Experience working in fast-paced, high-growth environments or large-scale tech organizations
Prior experience in a contractor or contingent workforce model

Responsibilities

Design, build, and maintain scalable data pipelines (batch and streaming) to support multiple business use cases
Develop and optimize ETL/ELT workflows, data models, and data warehouse architectures for efficient data processing
Implement data quality frameworks including validation, monitoring, and alerting to ensure data reliability
Create and maintain self-service dashboards and visualizations to communicate insights to stakeholders
Enable AI/ML-driven analytics by building feature pipelines and integrating model-ready datasets
Automate data workflows and reporting using AI tools to improve efficiency and reduce manual effort
Collaborate cross-functionally with product, engineering, and operations teams to deliver data-driven solutions
Attend regular internal practice community meetings
Collaborate with your itD practice team on industry thought leadership
Complete client case studies and learning material (blogs, media material)
Build out material to contribute to the Digital Transformation practice
Attend internal itD networking events (in person and virtual)
Work with leadership on career fast-track opportunities