Data Engineer

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💎 Seniority level: Middle, 4+ years

📍 Location: United States

💸 Salary: 112800.0 - 126900.0 USD per year

🔍 Industry: Software Development

🏢 Company: Titan Cloud

⏳ Experience: 4+ years

🪄 Skills: AWSPostgreSQLPythonSQLAgileApache AirflowCloud ComputingData AnalysisETLHadoopMySQLData engineeringData scienceREST APISparkCommunication SkillsAnalytical SkillsCI/CDProblem SolvingTerraformAttention to detailOrganizational skillsMicroservicesTeamworkData visualizationData modelingScripting

Requirements:

4+ years of work experience with ETL, Data Modeling, Data Analysis, and Data Architecture.
Experience operating very large data warehouses or data lakes.
Experience with building data pipelines and applications to stream and process datasets at low latencies.
MySQL, MSSQL Database, Postgres, Python

Responsibilities:

Design, implement, and maintain standardized data models that align with business needs and analytical use cases.
Optimize data structures and schemas for efficient querying, scalability, and performance across various storage and compute platforms.
Provide guidance and best practices for data storage, partitioning, indexing, and query optimization.
Developing and maintaining a data pipeline design.
Build robust and scalable ETL/ELT data pipelines to transform raw data into structured datasets optimized for analysis.
Collaborate with data scientists to streamline feature engineering and improve the accessibility of high-value data assets.
Designing, building, and maintaining the data architecture needed to support business decisions and data-driven applications. This includes collecting, storing, processing, and analyzing large amounts of data using AWS, Azure, and local tools and services.
Develop and enforce data governance standards to ensure consistency, accuracy, and reliability of data across the organization.
Ensure data quality, integrity, and completeness in all pipelines by implementing automated validation and monitoring mechanisms.
Implement data cataloging, metadata management, and lineage tracking to enhance data discoverability and usability.
Work with Engineering to manage and optimize data warehouse and data lake architectures, ensuring efficient storage and retrieval of structured and semi-structured data.
Evaluate and integrate emerging cloud-based data technologies to improve performance, scalability, and cost efficiency.
Assist with designing and implementing automated tools for collecting and transferring data from multiple source systems to the AWS and Azure cloud platform.
Work with DevOps Engineers to integrate any new code into existing pipelines
Collaborate with teams in trouble shooting functional and performance issues.
Must be a team player to be able to work in an agile environment

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Data Modeling

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Design schema and data pipelines to extract, transform, and load (ETL) data from various sources into the data warehouse or data lake.
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