Senior Data Engineer

Centillion Infotech
Glendale, CA, United States
24 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
9 years minimum
Working hours
Regular working hours
Job source

Tech stack

Agile Methodology Amazon Web Services Data Analysis Microsoft Azure Big Data BigQuery Cloud Computing Code Review Computer Programming Databases Continuous Integration Data Architecture
+29 more
Information Engineering Data Governance Extract Transform Load (ETL) Data Systems Data Warehousing DevOps Distributed Computing Environment Apache Hadoop Python (Programming Language) Meta-Data Management Scrum Methodology Standard Sql SQL Databases Enterprise Data Management Data Processing Google Cloud Real Time Systems Azure Data Factory Snowflake Apache Spark Git Data Lakes Information Technology AWS Glue Integration Frameworks Apache Kafka Data Management Data Pipelines Databricks

Job description

We are seeking an experienced Senior Data Engineer to design, develop, and optimize scalable data solutions that support business intelligence, analytics, and enterprise data initiatives. The ideal candidate will have strong expertise in data engineering, cloud platforms, ETL/ELT pipelines, data modeling, and big data technologies. This role requires collaboration with data analysts, architects, business teams, and engineering teams to deliver reliable and high-performance data solutions. Key Responsibilities

  • Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
  • Build and optimize data platforms, data warehouses, and data lakes.
  • Develop data integration solutions using batch and real-time processing frameworks.
  • Perform data modeling, transformation, cleansing, and validation activities.
  • Collaborate with business stakeholders and data analysts to understand data requirements.
  • Implement solutions using cloud-based data technologies and modern data architectures.
  • Optimize SQL queries, data processing jobs, and system performance.
  • Ensure data quality, security, governance, and compliance standards.
  • Troubleshoot complex data issues and provide root cause analysis.
  • Develop and maintain technical documentation for data solutions.
  • Participate in Agile ceremonies, design discussions, and code reviews.
  • Mentor junior engineers and contribute to best practices within the data engineering team.

Requirements

  • Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field.
  • 9-13 years of experience in Data Engineering, ETL development, and enterprise data solutions.
  • Strong programming experience with Python, SQL, and data processing frameworks.
  • Hands-on experience designing and developing ETL/ELT pipelines.
  • Strong experience with data warehousing concepts, data modeling, and database technologies.
  • Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
  • Experience with big data technologies and distributed processing systems.
  • Strong analytical, problem-solving, and communication skills.

Preferred Skills

  • Experience with Apache Spark, Hadoop, Kafka, Databricks, or Snowflake.
  • Experience with cloud data services such as AWS Glue, Azure Data Factory, BigQuery, or similar platforms.
  • Knowledge of data lake, lakehouse, and modern data architecture patterns.
  • Experience with CI/CD, DevOps practices, and automation.
  • Familiarity with data governance, metadata management, and data quality frameworks.
  • Experience working in Agile/Scrum environments.

Technical Skills

  • Python
  • SQL
  • ETL / ELT Development
  • Data Warehousing
  • Data Modeling
  • Data Lakes
  • Apache Spark
  • Databricks
  • Snowflake
  • Hadoop
  • Kafka
  • Cloud Platforms (AWS/Azure/GCP)
  • Azure Data Factory / AWS Glue
  • Database Technologies
  • API Integration
  • Git
  • CI/CD Pipelines
  • Agile/Scrum

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