TalentAQ

TalentAQ

Data Engineer

Data & AnalyticsFull Time2-7 yearsHyderabad, Telangana

Required Skills
17 skills

SQL
Python
Apache Airflow
Luigi
Spark
Hadoop
Hive
AWS
GCP
Azure
Redshift
BigQuery
Snowflake
Docker
Kubernetes
Kafka
Flink

Job Description

We seek a skilled Data Engineer to join our team and help build, maintain, and optimize data pipelines and architectures. You will work closely with data scientists, analysts, and software developers to ensure data availability, reliability, and performance for business-critical systems. Key Responsibilities: Design, construct, install, and maintain scalable and reliable data pipelines. Develop and optimize ETL (Extract, Transform, Load) processes. Build and maintain data architectures including databases, data warehouses, and large-scale processing systems. Collaborate with data scientists and analysts to understand data needs and deliver high-quality datasets. Ensure data quality, integrity, security, and compliance with governance standards. Monitor and troubleshoot data pipeline performance and reliability issues. Automate data validation and monitoring tasks. Document data workflows, processes, and infrastructure. Evaluate new data engineering tools and technologies.
We seek a skilled Data Engineer to join our team and help build, maintain, and optimize data pipelines and architectures. You will work closely with data scientists, analysts, and software developers to ensure data availability, reliability, and performance for business-critical systems. Key Responsibilities: Design, construct, install, and maintain scalable and reliable data pipelines. Develop and optimize ETL (Extract, Transform, Load) processes. Build and maintain data architectures including databases, data warehouses, and large-scale processing systems. Collaborate with data scientists and analysts to understand data needs and deliver high-quality datasets. Ensure data quality, integrity, security, and compliance with governance standards. Monitor and troubleshoot data pipeline performance and reliability issues. Automate data validation and monitoring tasks. Document data workflows, processes, and infrastructure. Evaluate new data engineering tools and technologies.

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