Data Engineer

RresolveExpert Solutions LLC

United States

3 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Application Programming Interfaces (APIs) Agile Methodology Amazon Web Services Microsoft Azure Business Intelligence Development Big Data BigQuery Software as a Service Cloud Computing Databases Continuous Integration Information Engineering

+28 more

Data Integration Extract Transform Load (ETL) Data Mart Data Security Data Warehousing Relational Databases Distributed Computing Environment Python (Programming Language) PostgreSQL Microsoft SQL Server MySQL Oracle (Applications) Software Deployment SQL Databases Google Cloud Data Ingestion Snowflake Apache Spark Git Data Lakes Pyspark Information Technology Data Management Azure Synapse Analytics Software Version Control Data Pipelines Docker Amazon Redshift

Job description

We are seeking a skilled Data Engineer to design, develop, and maintain scalable data pipelines and data platforms. The ideal candidate will have strong experience with SQL, Python, cloud technologies, ETL/ELT processes, data warehousing, and distributed data processing., * Design, build, and maintain scalable ETL/ELT data pipelines.

Develop reliable data ingestion and transformation workflows using Python and SQL.
Build and optimize data warehouses, data lakes, and data marts.
Work with large datasets using technologies such as Spark, PySpark, or similar distributed processing frameworks.
Develop data pipelines using cloud platforms such as AWS, Azure, or Google Cloud Platform.
Implement data quality, validation, monitoring, and error-handling processes.
Optimize SQL queries, data models, and pipeline performance.
Integrate data from APIs, databases, SaaS applications, and other structured/unstructured sources.
Collaborate with Data Scientists, BI Developers, Analysts, Software Engineers, and business stakeholders.
Implement CI/CD, version control, testing, and deployment best practices for data engineering workflows.
Ensure data security, governance, privacy, and compliance requirements are followed.
Troubleshoot data pipeline failures and resolve production issues.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.
10+ years of professional experience in data engineering or a related field.
Strong proficiency in SQL and Python.
Experience developing ETL/ELT pipelines and working with data integration tools.
Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud.
Experience with data warehousing technologies such as Snowflake, BigQuery, Redshift, or Azure Synapse.
Experience with Apache Spark/PySpark or other distributed processing technologies.
Familiarity with Git, CI/CD, Docker, and Agile development practices.
Strong analytical, troubleshooting, and communication skills.