DeepSource Technologies

Information Technology and Services

L1DataEngineer

United Kingdom FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Entry candidates.

The Brief

“L1 Data Engineer at DeepSource Technologies. Skills: Data Pipelines, ETL/ELT, Databricks, Azure. Design data pipelines. Develop data pipelines”

Industry & Context.

Information Technology and Services
Problems you'll solve

troubleshoot pipeline failures; resolve data quality issues; root-cause analysis

What They're Looking For.

Must Have

Python for data processing, Pandas for data manipulation, PySpark for distributed data processing, Databricks, Azure Data Factory, Azure Synapse Analytics, Spark pool integration, SQL skills, query writing, query optimization, performance tuning, incremental loading, data lake architecture, Delta Lake, data governance concepts, security concepts

Nice to Have

SQL Server migration projects, schema conversion, data movement, Terraform for Azure infrastructure provisioning, CI/CD practices for data engineering, Delta Sharing, Lakehouse Federation concepts

What You'll Do.

Design data pipelines

Develop data pipelines

Maintain data pipelines

Build data ingestion processes

Optimize data ingestion processes

Transform large datasets

Process large datasets

Write complex SQL queries

Optimize complex SQL queries

Implement data models

Monitor pipeline failures

Troubleshoot pipeline failures

Resolve data quality issues

Contribute to documentation

Support tool evaluation

How You'll Work.

Team & Collaboration

Collaborate with data architects; Collaborate with senior engineers; Support the team

Full Job Description

We are looking for a motivated and technically solid L1 Data Engineer to join our growing Data & Analytics team. In this role, you will be responsible for designing, building, and maintaining the data architecture and infrastructure that supports our organization's data strategy. You will work hands-on to develop, test, and deploy reliable data solutions — ensuring pipelines are scalable, efficient, and aligned with business requirements. This is an ideal opportunity for a data professional who is eager to deepen their expertise in cloud-native data platforms, particularly within the Microsoft Azure and Databricks ecosystem, and who thrives in a collaborative, fast-paced environment. **KEY RESPONSIBILITIES** • Design, develop, and maintain scalable data pipelines and ETL/ELT workflows to support business intelligence and analytics use cases. • Build and optimize data ingestion processes using Azure Data Factory and Databricks, ensuring data quality and consistency across all layers of the data platform. • Transform and process large datasets using PySpark and Python, applying best practices for performance and maintainability. • Write and optimize complex SQL queries to support analytical reporting and data validation requirements. • Collaborate with data architects and senior engineers to implement and maintain data models aligned with organizational standards. • Monitor, troubleshoot, and resolve pipeline failures and data quality issues, applying root-cause analysis to prevent recurrence. • Contribute to documentation of data pipelines, data dictionaries, and engineering standards. • Support the team in exploring and evaluating new tools and approaches to continuously improve the data infrastructure. **Requirements** * 2+ years of professional experience in a Data Engineering or closely related role. * Strong proficiency in Python for data processing, transformation, and automation tasks. * Hands-on experience with Pandas for data manipulation and PySpark for dis

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