Key Facts

Remote From:

Full time

Senior (5-10 years)

English

Hard Skills

Apache Airflow Snowflake (Data Warehouse) SQL (Programming Language) Python (Programming Language) Data Quality Assessment Cloud Computing Data Transformation Data Validation AWS Cloud Services Sales Reporting Process Migration Batch Processing Operational Support And Analysis Data Architecture Data Migration Automated Testing Framework Data Architecture Internal Documentation

Other Skills

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Collaboration
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Communication
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Teamwork
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Knowledge Transfer
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Problem Solving

Data Meaning

About Data Meaning

Data Meaning is a consulting company that provides business intelligence services to leading companies and government agencies. Our mission is to increase the effectiveness of our customers' business, without compromising their budget, by transforming data into intelligent information that will lead into strategic decisions. We provide top consultant services that generate flexible solutions to our clients in the areas of Business Intelligence, Data Warehousing and Project Management. Our offer includes short and long-term contracts, employee placement, and outsourcing strategies to better comply with our customers' needs and goals.

Company type: SME

Founded: 2018

Company size: 51 - 200

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Job description

Senior Data Engineer

Location: Remote, US based
Position type: TBD

Job Summary

Data Meaning is a front-runner in Business Intelligence and Data Analytics consulting, renowned for our high-quality consulting services throughout the US and beyond. Our expertise lies in delivering tailored solutions in Business Intelligence, Data Warehousing, and Project Management. We have a diverse, global team of consultants, all working remotely, embodying a collaborative, inclusive, and innovation-driven work culture.
As part of our growth and upcoming initiatives, we are proactively searching for Senior Data Engineers to support future projects and platform modernization efforts across our client portfolio.

Position Summary
The Senior Data Engineer will play a key role in supporting the transition and modernization of the client’s data platform. The position will focus on pipeline migration, operational stabilization, and the implementation of a dbt-based transformation framework within a Snowflake environment.

This role will work closely with the Lead Data Architect and the client’s engineering team, participating in knowledge transfer sessions.

Key Responsibilities:

Develop and maintain ELT pipelines using Snowflake, Python, and Apache Airflow
Implement data ingestion and transformation logic for batch and incremental pipelines
Convert existing SQL transformations into dbt models
Implement dbt testing frameworks (schema, relationship, freshness tests)
Participate in pipeline walkthroughs and knowledge transfer sessions with the existing team
Document data pipelines and operational procedures
Support the transition from vendor-managed pipelines to Data Meaning ownership
Monitor production pipelines and data workflows
Troubleshoot pipeline failures and operational issues
Improve monitoring, alerting, and operational reliability
Implement automated data validation and quality checks
Support the development of a data quality framework

Required Skills & Qualifications:

Advanced/fluent english
8+ years of experience in Data Engineering
Hands-on experience with Snowflake
Experience working with Apache Airflow
Strong SQL (advanced) skills
Strong Python programming skills
Experience building: ELT pipelines, Data warehouse transformations, Batch and incremental, pipelines, Data ingestion pipelines
Experience working in cloud environments (AWS preferred)