jobapplier

Senior Data Engineer - Contract

Reailize

Skills

Required

  • data engineering
  • window functions
  • complex joins
  • query optimization
  • BigQuery
  • data processing
  • automation
  • GitHub
  • GCP / AWS / Azure
  • Docker
  • Kubernetes
  • Terraform

Preferred

  • Dataform
  • Semantic-layer design
  • LookML
  • Grafana
  • Superset
  • dbt
  • data transformation
  • Design analytical data models
  • star schema
  • Domino

About the role B-Yond is hiring a Senior Data Engineer to lead the technical delivery of a data and analytics program for a large enterprise telecom customer. You'll own the work from ingestion through to dashboards. You'll be the main technical contact with the customer's data and engineering teams, and you'll work with a distributed team that uses AI-assisted development every day. This is a 6 months contract with a potential to extend. Please note that candidates must be based in the United States and available to travel to customer locations as required.

About Reailize

  • Us Join Reailize – where innovation meets impact.
  • We’re on a mission to help global enterprises work smarter, faster, and more efficiently at the cutting edge of AI, data, and cloud .
  • By combining deep expertise, advanced engineering, and patented software, we transform complexity into opportunity.
  • Here, curiosity, collaboration, and bold ideas aren’t just welcomed – they’re celebrated.

What makes us different?

We are a private & global group of companies with 20+ years of proven track record , supporting leading organizations in Telecom, Security, and Real Estate across North America, Europe, the Middle East, and Latin America .

Responsibilities

  • Lead the design, build and operation of scalable data transformation pipelines over large data volumes.
  • Design analytical data models (star schema, fact and dimension tables, aggregation layers) that serve reporting and dashboards.
  • Build and maintain dashboards in Looker or similar BI tools, working with stakeholders on metrics, layout and usability.
  • Build reliable incremental processing, including late-arriving data, deduplication, reprocessing and backfills.
  • Define and run data quality checks, validation rules and pipeline observability (monitoring, alerting, lineage).
  • Optimize pipelines and queries for performance and cost.
  • Work with stakeholders to turn business requirements into data models and metric definitions.
  • Set the engineering standards for the project (code reviews, branching, testing, CI/CD, documentation) and keep them aligned with the client's security, data governance and engineering policies.
  • Work on site with the customer for workshops, design sessions and key milestones.
  • Mentor other engineers and help with estimation, planning and technical risk management.
  • unit tests for transformations, schema and data contract tests, data quality assertions, regression checks.
  • Spark (PySpark).
  • DataOps and enterprise data science platforms such as Domino, Databricks or similar, including MLOps workflows.

Requirements

  • 6+ years in data engineering, including 3+ years building production pipelines over large-scale datasets.
  • window functions, complex joins, query optimization and incremental patterns.
  • Hands-on BigQuery experience.
  • Python for data processing, automation and testing.
  • star and snowflake schemas, fact and dimension tables, slowly changing dimensions, grain definition, aggregations and rollups.
  • Hands-on experience building production dashboards in Looker or another BI tool (Tableau, Power BI or similar).
  • Working knowledge of the wireless telecom domain.
  • You don't need to be a telco expert, but you should understand how a mobile operator is organized and its main network and operations functions.
  • Experience across the full software development lifecycle: requirements, design, implementation, testing, release and support.
  • Git workflows, pull request reviews, automated deployments across environments.
  • Practical use of AI-assisted development tools (for example Claude Code, GitHub Copilot or Cursor) for coding, testing, documentation and review, along with good judgment in validating and securing AI-generated output.
  • Experience working within enterprise client policies on security, compliance and data governance.
  • Good communication in English and comfort working directly with enterprise customers.
  • Based in the United States and able to travel to customer sites.
  • Airflow.
  • Data lake and lakehouse architectures (Parquet, Delta/Iceberg).
  • Cloud data platforms (GCP, AWS or Azure).
  • Docker and Kubernetes.
  • Infrastructure as code (Terraform).
  • Experience handling sensitive or regulated data (masking, access controls, privacy requirements).

Preferred

  • Dataform, dbt.
  • Semantic-layer design (for example LookML) and additional BI tools (Grafana, Superset).

Interview Integrity

During the interview process, we're evaluating your individual problem-solving skills, creativity, and approach to challenges. While AI tools like ChatGPT, Claude, and Cursor are part of your daily toolkit once you join B-Yond, all interviews, assessments, and take-home assignments must be completed independently. You may not use AI tools, third-party services, coaching platforms, or content-farming services during any part of the interview process unless we explicitly permit it. We will clearly communicate when AI tools are allowed for specific assessments. Any indication of third-party assistance or AI-generated responses will result in immediate disqualification.