Job Title:

Data Engineer

Job Description

Key Responsibilities:

Data Pipeline Development:
Design, build, and manage scalable, reliable, and efficient ETL/ELT data pipelines to ingest, process, and store large datasets from various data sources.Data Integration:
Integrate data from different sources such as APIs, relational databases, NoSQL databases, flat files, and streaming data into centralized data lakes or data warehouses.Database Management & Optimization:
Implement and maintain data storage solutions such as relational databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), and cloud-based data warehouses (e.g., Amazon Redshift, Google BigQuery).Data Quality & Validation:
Ensure data quality and integrity through the design and implementation of data validation, cleansing, and enrichment processes. Identify and address data discrepancies and inconsistencies.Collaboration with Teams:
Collaborate with data scientists, analysts, and software engineers to understand data requirements, and deliver data solutions that meet analytical and operational needs.Performance Tuning:
Optimize data pipelines and data storage systems for maximum efficiency, scalability, and performance. Proactively monitor system performance and troubleshoot issues.Data Governance & Security:
Work closely with the data governance and security teams to ensure that data solutions comply with organizational standards, privacy laws (e.g., GDPR, CCPA), and security policies.Cloud Data Engineering:
Design and manage data workflows in cloud environments such as AWS, Azure, or Google Cloud, utilizing cloud-native services for data processing and storage.Automation & Scheduling:
Automate data workflows and implement scheduling tools (e.g., Airflow, Cron) to ensure timely data delivery for reports, dashboards, and analytics.Documentation:
Create and maintain technical documentation for data pipelines, data models, and data management processes to ensure knowledge sharing and reproducibility.

Requirements:

Education:
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Technology, or a related field.Experience:Minimum of 3-5 years of experience in data engineering, ETL development, or database management.Experience with cloud platforms and cloud-native data processing tools.Skills & Expertise:Proficiency with SQL for querying and manipulating data.Experience with data integration tools (e.g., Apache Airflow, Talend, Informatica) and ETL/ELT processes.Strong programming skills in Python, Java, or Scala for data processing.Knowledge of big data technologies (e.g., Hadoop, Spark, Kafka).Experience with data warehousing solutions (e.g., Snowflake, Amazon

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Location:

MEX Work-at-Home

Language Requirements:

Time Type:

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