Data Engineer -5

Realign LLC

Charlotte (NC)

On-site

USD 88,000 - 108,000

Full time

3 days ago

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Job summary

Realign LLC is seeking an on-site Data Engineering PROD support professional in Charlotte, NC to manage data pipelines, ensure data quality, and resolve production issues across multiple tech stacks. The role emphasizes security, governance, and observability while collaborating with analytics teams.

The candidate should bring 5+ years in data/ software engineering, strong PySpark, SQL, Python, and experience with Spark ecosystems and cloud platforms.

Qualifications

5 to 10 years in Data Engineering, Software Engineering, or a related technical discipline
Strong proficiency in PySpark, Python, SQL, and distributed data processing tools
Hands-on experience building ETL/ELT pipelines and data ingestion processes

Responsibilities

Implement efficient data flows and enforce data management standards
Enhance data quality while supporting continuous delivery and release cycles
Perform root-cause analysis for production issues across multiple technology stacks
Troubleshoot and fix performance issues
Support Dev work related to App Gov and other mandates
Analyze and resolve pipeline issues, performance bottlenecks, and data discrepancies
Adhere to enterprise data governance, compliance, and operational risk frameworks
Contribute to monitoring and observability for data pipelines (logs, metrics, health checks)
Support analytical workloads, BI tools, or data science teams
Apply data security practices including encryption, masking, and PII handling

Skills

PySpark

Hive

Python

SQL

Hadoop

Apache Spark

Databricks

Teradata

Snowflake

SQL Server

Azure

AWS

GCP

Git

CI/CD

App Gov

Unix

ETL/ELT

Tools

Databricks

Teradata

Snowflake

Azure

AWS

GCP

Git

CI/CD

Job description

Realign LLC is hiring for an on-site Data Engineering PROD support role in Charlotte, NC.

Responsibilities

Implement efficient data flows and enforce data management standards
Enhance data quality while supporting continuous delivery and release cycles
Perform root-cause analysis for production issues across multiple technology stacks
Troubleshoot and fix performance issues
Support Dev work related to App Gov and other mandates
Analyze and resolve pipeline issues, performance bottlenecks, and data discrepancies
Adhere to enterprise data governance, compliance, and operational risk frameworks
Contribute to monitoring and observability for data pipelines (logs, metrics, health checks)
Support analytical workloads, BI tools, or data science teams
Apply data security practices including encryption, masking, and PII handling

Requirements

Experience: 5 to 10 years in Data Engineering, Software Engineering, or a related technical discipline
Primary skills: PySpark, Hive, Python, SQL, Hadoop
Python and SQL: strong proficiency for advanced data transformations
Hands-on experience designing and building ETL/ELT pipelines, data ingestion processes, and distributed data processing jobs
Practical experience with distributed data tools such as Apache Spark, Databricks, or Hadoop ecosystems
Experience building and managing datasets in relational and/or cloud-based platforms including Teradata, Snowflake, SQL Server, Azure, AWS, and GCP
Solid understanding of data modeling, metadata, data quality controls, data lineage, and secure data management
Experience contributing to automated test suites, analyzing test failures, and supporting test-driven development
Knowledge of CI/CD pipelines, version control with Git, and automated deployment practices
Strong communication skills and ability to collaborate across engineering, product, and business teams
Advanced experience with performance tuning of SQL, Spark, or distributed data workflows
Ability to troubleshoot pipeline issues, performance bottlenecks, and data discrepancies
Prior experience in a financial institution or another regulated industry
Secondary: Unix, Agile, Base support