Senior Data Engineer – Cloud & Analytics

Mogi I/O : OTT/Podcast/Short Video Apps for you; City of Kingston (NY); On-site; USD 120,000 - 140,000; Full time

Job summary

A leading technology company is seeking a Sr. Data Engineer to drive its data initiatives across various teams. The ideal candidate will design and implement scalable data pipelines, optimize SQL queries, and ensure data quality across a growing ecosystem. Candidates should have expertise in Advanced SQL, Python, and cloud platforms. This role is essential for leveraging data to support business growth and requires strong analytical skills. Successful applicants can expect a competitive salary between $120,000 and $140,000.

Qualifications

• 8–15 years of experience in data engineering.
• Experience with designing and implementing scalable data pipelines.
• Familiarity with cloud platforms required.

Responsibilities

• Collect and integrate data from internal/external sources.
• Design table structures and build ETL pipelines.
• Implement automated data quality checks.
• Optimize SQL queries and ETL processes.
• Support ad hoc analysis and database deployments.

Skills

Advanced SQL

Python

Spark

Snowflake

Databricks

Cloud platforms (AWS/Azure/GCP)

Problem-solving skills

Analytical skills

Communication skills

Familiarity with Agile Scrum

Tools

Airflow

Prefect

Docker

Monitoring tools (Datadog)

CI/CD tools

Kafka

Job description

Job Title

Sr. Data Engineer

Location

USA – New York, Santa Monica, Seattle

Experience

8–15 Years

Salary

USD 120,000 – 140,000

Job Overview

The Sr. Data Engineer will drive the company’s data initiatives by partnering with business, analytics, and infrastructure teams to design and implement scalable data pipelines. The role involves identifying data sources, designing table structures, building ETL pipelines, implementing automated data quality checks, and ensuring reliable, high-performance data solutions across a fast-growing data ecosystem.

Key Responsibilities

• Collect and integrate data from internal/external sources.
• Design table structures and build ETL pipelines (Airflow/Prefect).
• Implement automated data quality checks.
• Optimize SQL queries and ETL processes.
• Support ad hoc analysis and database deployments.

Must-Have Skills

• Advanced SQL, Python, Spark, Snowflake, Databricks.
• Experience with cloud platforms (AWS/Azure/GCP).
• Strong problem-solving, analytical, and communication skills.
• Familiarity with Agile Scrum.

Nice-to-Have

• Data modeling, Kafka, CI/CD tools, Docker, monitoring tools (Datadog).