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Job Details

Skills

Analytical Skill
PySpark
SQL
Semantics
Reporting
Query Optimization
Python
Orchestration
Data Lake
BigQuery
Looker
PowerBI
CI/CD
Data Pipelines
Dataform
dbt
Spark (PySpark)
Domino
Databricks
MLOps workflows
Airflow
lakehouse architectures (Parquet
Delta/Iceberg)
GCP
AWS
Azure
Docker
Kubernetes
Terraform
LookML
Grafana
Superset

Summary

Job Title - Sr. Data Engineer

Location - Remote

Length - Contract (6 Months+)

Overview -

Senior Data Engineer - 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.

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 (Google Cloud Platform, 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).

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: apn
Position Id: Data Engineer_Byond
Posted 7 days ago

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Contact the job poster

Kushal Shah

Talent Acquisition Consultant @ APN Software Services, Inc

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