Senior Data Engineer - Contract

Join 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 .

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.

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.

Qualifications

• 6+ years in data engineering, including 3+ years building production pipelines over large-scale datasets.
• Advanced SQL: window functions, complex joins, query optimization and incremental patterns.
• Hands-on BigQuery experience.
• Strong Python for data processing, automation and testing.
• Solid dimensional modeling: 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.
• Automated testing for data: unit tests for transformations, schema and data contract tests, data quality assertions, regression checks.
• CI/CD for data pipelines: 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.

Nice to have

• Transformation frameworks: Dataform, dbt.
• Distributed processing: Spark (PySpark).
• DataOps and enterprise data science platforms such as Domino, Databricks or similar, including MLOps workflows.
• Orchestration: Airflow.
• Data lake and lakehouse architectures (Parquet, Delta/Iceberg).
• Cloud data platforms (GCP, AWS or Azure).
• Docker and Kubernetes.
• Infrastructure as code (Terraform).
• Semantic-layer design (for example LookML) and additional BI tools (Grafana, Superset).
• Experience handling sensitive or regulated data (masking, access controls, privacy requirements).

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.