Data Engineer
Robotics Technologies LLC
Dallas, TX, United States
3 days ago
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Role details
Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$174,720
Working hours
Regular working hours
Job source
Tech stack
Query Performance
Agile Methodology
Airflow
Amazon Web Services
Microsoft Azure
Big Data
Cloud Database
Computer Programming
Databases
Continuous Integration
Data Validation
Information Engineering
+37 more
Data Governance
Data Integration
Extract Transform Load (ETL)
Data Security
Data Warehousing
Software Debugging
Dimensional Modeling
Distributed Computing Environment
Distributed Systems
Apache Hadoop
Python (Programming Language)
Meta-Data Management
NoSQL
Operational Databases
Cloud Services
SQL Databases
Unstructured Data
Google Cloud
Cloud Platform System
Data Ingestion
Azure Data Factory
Snowflake
Apache Spark
Git
Pyspark
Kubernetes
Information Technology
AWS Glue
Google Bigquery
Integration Frameworks
Apache Kafka
Data Management
Video Streaming
Data Pipelines
Docker
Amazon Redshift
Databricks
Job description
The Data Engineer will build, maintain, and optimize scalable data platforms and pipelines to support enterprise analytics and business intelligence initiatives. This role focuses on data integration, transformation, processing, and cloud-based data architecture while ensuring data quality, reliability, and performance., * Design, develop, and maintain scalable ETL/ELT data pipelines.
- Build data ingestion and transformation workflows from multiple sources.
- Process large datasets using Python, SQL, PySpark, and Spark.
- Develop and optimize data warehouse and lakehouse solutions.
- Implement data validation, reconciliation, and quality checks.
- Integrate structured and unstructured data from enterprise systems.
- Optimize query performance and improve data pipeline efficiency.
- Monitor pipeline execution, troubleshoot failures, and resolve data issues.
- Implement data security, governance, and access-control standards.
- Collaborate with data scientists, analysts, architects, and business stakeholders.
Requirements
- Strong programming experience with Python, SQL, and PySpark.
- Hands-on experience with ETL/ELT development and data pipeline architecture.
- Knowledge of Apache Spark, Hadoop, and distributed data processing.
- Experience with cloud data platforms such as AWS, Azure, or Google Cloud.
- Familiarity with Snowflake, Databricks, Amazon Redshift, or Google BigQuery.
- Experience with data orchestration tools such as Apache Airflow, Azure Data Factory, or AWS Glue.
- Strong understanding of relational and NoSQL databases.
- Knowledge of data modeling, data warehousing, and dimensional modeling.
- Experience with Kafka or other streaming technologies is preferred.
- Familiarity with Git, Docker, Kubernetes, and CI/CD pipelines.
- Understanding of data governance, metadata management, and data security., * 5+ years of experience in data engineering or big data development.
- Strong hands-on experience building and supporting production data pipelines.
- Experience working with cloud-based data platforms and enterprise databases.
- Understanding of distributed computing and data processing frameworks.
- Strong analytical, debugging, and problem-solving abilities.
- Experience working in Agile development environments., * Bachelorβs degree in Computer Science, Information Technology, Data Engineering, or a related field.
- Masterβs degree is preferred.
- Certifications in AWS, Azure, Google Cloud, Snowflake, or Databricks are an advantage.
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