Senior Data Engineer

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.

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.