Data Platform Engineer: ETL, Pipelines & Analytics

Kyndryl Inc.; Dallas, Northern (TX, KY); Hybrid; USD 73,000 - 140,000; Full time

Benefits offered by this job

Discretionary bonus

Benefits package

Job summary

Kyndryl is seeking a Data Engineer to design, build and optimize data platforms that empower decision-makers with clean, harmonized data. You will turn raw information into reliable datasets and partner with business teams to translate requirements into scalable data pipelines.

The role covers ETL, data mining, and data storage with tools such as Glue, Databricks, Synapse or Dataproc, plus relational and NoSQL databases like PostgreSQL, DB2, MongoDB and SQL Server.

Qualifications

• Expertise in data mining, data storage and ETL processes.
• Experience with data pipelines development and tooling (Glue, Databricks, Synapse, Dataproc).
• Experience with relational and NoSQL databases (PostgreSQL, DB2, MongoDB, SQL Server).
• Strong problem-solving, analytical and communication skills.

Responsibilities

• Design, build, and optimize data platforms and pipelines to deliver clean, harmonized data for analytics.
• Transform raw data into refined datasets and ensure data quality and governance.
• Collaborate with business teams to translate requirements into scalable data solutions and analytics workflows.
• Monitor data quality and implement lifecycle management to keep data fresh and reliable.

Skills

ETL processes

Data pipelines

Glue

Databricks

Synapse

Dataproc

PostgreSQL

DB2

MongoDB

SQL Server

Problem solving

Analytical thinking

Communication skills

Project management

Education

Bachelor's degree in Computer Science/Information Technology

Job description

Kyndryl is seeking a Data Engineer to design, build and optimize data platforms that empower decision-makers with clean, harmonized data. You will turn raw information into reliable datasets and partner with business teams to translate requirements into scalable data pipelines.

The role covers ETL, data mining, and data storage with tools such as Glue, Databricks, Synapse or Dataproc, plus relational and NoSQL databases like PostgreSQL, DB2, MongoDB and SQL Server.