Mid Data Engineer - Poland, Polska - Strategic Staffing Solutions

Opis

Strategic Staffing Solutions is looking for Data Engineer to support a global US Customer in oil and gas industry. Fully remote from Poland with optional annual trip to US HQ.

The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.

Responsibilities for Data Engineer Create and maintain optimal data pipeline architecture, Assemble large, complex data sets that meet functional / non-functional business requirements.

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data technologies.

Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

Work with data and analytics experts to strive for greater functionality in our data systems.

Qualifications for Data Engineer Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.

Experience building and optimizing big data data pipelines, architectures and data sets.

Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.

Strong analytic skills related to working with unstructured datasets.

Build processes supporting data transformation, data structures, metadata, dependency and workload management.

A successful history of manipulating, processing and extracting value from large disconnected datasets.

Working knowledge of message queuing, stream processing, and highly scalable big data data stores.

Strong project management and organizational skills.

Experience supporting and working with cross-functional teams in a dynamic environment.

Data engineer will join surface maintenance & inspection product line integration team to build and enhance robust data integration solutions to better support other product teams.

Experience with data acquisition, preparation and validation, data movement and transformation in Azure cloud for data integration and ETL processes.

Experience with Azure cloud services including Azure SQL Database, Azure Blob Storage, Azure Data Lake, Azure Data Factory, Azure Synapse.

Proficiency in big data technologies such as Spark, Hadoop, or Kafka Strong expertise in SQL and data warehousing solutions.

Strong programming language skill like Python for data processing.

Familiar with ADO CICD pipeline and ansible.

Strategic Staffing Solutions is looking for Data Engineer to support a global US Customer in oil and gas industry. Fully remote from Poland with optional annual trip to US HQ.

The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.

Responsibilities for Data Engineer Create and maintain optimal data pipeline architecture, Assemble large, complex data sets that meet functional / non-functional business requirements.

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data technologies.

Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

Work with data and analytics experts to strive for greater functionality in our data systems.

Qualifications for Data Engineer Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.

Experience building and optimizing big data data pipelines, architectures and data sets.

Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.

Strong analytic skills related to working with unstructured datasets.

Build processes supporting data transformation, data structures, metadata, dependency and workload management.

A successful history of manipulating, processing and extracting value from large disconnected datasets.

Working knowledge of message queuing, stream processing, and highly scalable big data data stores.

Strong project management and organizational skills.

Experience supporting and working with cross-functional teams in a dynamic environment.

Data engineer will join surface maintenance & inspection product line integration team to build and enhance robust data integration solutions to better support other product teams.

,[Design, build, and maintain scalable data warehouses and big data solutions using Azure Synapse Analytics., Develop and optimize data pipelines integrating various data sources into Synapse., Monitor system performance and perform query performance tuning for large-scale data queries, troubleshoot issues, and ensure system reliability and data accuracy.

] Requirements:

Azure Cloud, ETL, Azure SQL Database, Blob Storage, Azure Data Lake, Azure Data Factory, Azure Synapse, Big data, Spark, Hadoop, Kafka, SQL, Data warehouse, Python, CI/CD Pipelines, Ansible,

Azure Additionally:
Training budget.