Omni Inclusive
Data Engineer
Omni Inclusive, Dallas, Texas, United States, 75215
We are seeking a talented Data Engineer with 7+ years of experience to join our team in the telecom industry. The ideal candidate will have a strong background in data engineering, with specific experience in telecom data processing, ETL development, and data pipeline optimization. You will work closely with our data scientists and business analysts to help drive data-driven decisions and support our telecom operations.
Key Responsibilities Design, develop, and maintain scalable data pipelines and ETL processes for telecom data. Work with large datasets from telecom operations, including call records, network performance metrics, and customer usage data. Develop and maintain efficient data processing architectures to support real-time data ingestion and transformation. Develop and maintain an ontology model to represent relationships between telecom entities (e.g., accounts, devices, transactions) for fraud analysis. Design efficient, reusable queries to support relational data exploration within the Graph DB, enabling fraud detection and pattern recognition. Analysis of the graph extracts to ensure alignment to use case requirements. Exploratory data analysis for all the data sources to meet use case requirements Optimize data storage and retrieval mechanisms to support data analytics and reporting needs. Collaborate with cross-functional teams (data science, product, and engineering) to understand data requirements and deliver solutions. Ensure data quality and integrity through robust monitoring, validation, and troubleshooting practices. Implement and manage data security practices, including encryption and access control, in compliance with telecom industry standards. Required Skills & Qualifications
Bachelor's degree in Computer Science, Engineering, or a related field. 3-5 years in data engineering, with a focus on telecom or similar data-intensive domains. Technical Skills:
Proficiency in SQL and experience with data warehouses (e.g., Snowflake, Redshift, BigQuery). Strong experience in programming languages like Python and Scala for data processing. Familiarity with big data frameworks such as Apache Spark, Hadoop, or similar. Knowledge of ETL tools (e.g., Informatica, Talend, Apache NiFi) is preferable. Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud (GCP) for data solutions is preferable . Understanding of telecom-specific data sources and structures (e.g., call data records, network KPIs) is advantage.
Strong experience with data integration, data modeling, and data governance. Excellent analytical skills with keen attention to detail. Ability to convey complex technical information effectively to stakeholders. Preferred Qualifications
Experience with data visualization tools (e.g., Tableau, Power BI) is a plus. Knowledge of telecom protocols, standards, and metrics is a strong advantage. Certification in cloud technologies or data engineering (e.g., AWS Certified Data Analytics, Google Professional Data Engineer) is a plus
Key Responsibilities Design, develop, and maintain scalable data pipelines and ETL processes for telecom data. Work with large datasets from telecom operations, including call records, network performance metrics, and customer usage data. Develop and maintain efficient data processing architectures to support real-time data ingestion and transformation. Develop and maintain an ontology model to represent relationships between telecom entities (e.g., accounts, devices, transactions) for fraud analysis. Design efficient, reusable queries to support relational data exploration within the Graph DB, enabling fraud detection and pattern recognition. Analysis of the graph extracts to ensure alignment to use case requirements. Exploratory data analysis for all the data sources to meet use case requirements Optimize data storage and retrieval mechanisms to support data analytics and reporting needs. Collaborate with cross-functional teams (data science, product, and engineering) to understand data requirements and deliver solutions. Ensure data quality and integrity through robust monitoring, validation, and troubleshooting practices. Implement and manage data security practices, including encryption and access control, in compliance with telecom industry standards. Required Skills & Qualifications
Bachelor's degree in Computer Science, Engineering, or a related field. 3-5 years in data engineering, with a focus on telecom or similar data-intensive domains. Technical Skills:
Proficiency in SQL and experience with data warehouses (e.g., Snowflake, Redshift, BigQuery). Strong experience in programming languages like Python and Scala for data processing. Familiarity with big data frameworks such as Apache Spark, Hadoop, or similar. Knowledge of ETL tools (e.g., Informatica, Talend, Apache NiFi) is preferable. Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud (GCP) for data solutions is preferable . Understanding of telecom-specific data sources and structures (e.g., call data records, network KPIs) is advantage.
Strong experience with data integration, data modeling, and data governance. Excellent analytical skills with keen attention to detail. Ability to convey complex technical information effectively to stakeholders. Preferred Qualifications
Experience with data visualization tools (e.g., Tableau, Power BI) is a plus. Knowledge of telecom protocols, standards, and metrics is a strong advantage. Certification in cloud technologies or data engineering (e.g., AWS Certified Data Analytics, Google Professional Data Engineer) is a plus