Role overview

Senior Data Engineer

Requirements and responsibilities

Readable role content extracted into sections for faster review.

Key Responsibilities

  • Design and develop robust, scalable data pipelines using Azure Data Factory (ADF)
  • Build and optimize data processing workflows using Databricks and Apache Spark
  • Implement declarative pipeline solutions using Lakehouse architecture and best practices
  • Write and optimize complex SQL queries for data transformation and analysis
  • Develop PySpark applications for large-scale data processing
  • Collaborate with data scientists, analysts, and stakeholders to understand data requirements
  • Ensure data quality, security, and compliance across all pipelines
  • Monitor, troubleshoot, and optimize data pipeline performance
  • Document technical solutions and maintain best practices documentation
  • Mentor junior team members and contribute to team knowledge sharing

What we're Looking For

  • Proficient in building scalable data solutions using Azure and Databricks
  • Skilled in SQL and PySpark for data transformation and processing
  • Capable of implementing declarative, maintainable pipeline architectures
  • Detail-oriented with a focus on data quality and performance optimization
  • Collaborative and able to work effectively with cross-functional teams
  • Proactive in staying current with emerging data engineering technologies and best practices
  • Communicative and able to explain complex technical concepts clearly

Must-Have Technical Skills

  • Azure Data Factory (ADF)“ Proven experience designing and implementing data integration solutions
  • Databricks“ Hands-on experience with Databricks platform and workspace management
  • Apache Spark “ Strong expertise in distributed data processing using Spark framework
  • Lakeflow & Declarative Pipelines – Experience building declarative, maintainable data pipelines
  • SQL – Advanced proficiency in writing optimized SQL queries for complex data transformations
  • PySpark “ Strong programming skills in PySpark for data processing and ETL operations

Additional Desired Qualifications:

  • Experience with cloud platforms (Azure, AWS, or GCP)
  • Knowledge of data warehousing concepts and modern data architecture
  • Familiarity with version control systems (Git)
  • Understanding of CI/CD pipelines and DevOps practices
  • Experience with data quality frameworks and testing methodologies
  • Knowledge of big data technologies and distributed computing

Required Experience

  • 5+ years of professional experience in data engineering or related roles
  • 3+ years of hands-on experience with cloud-based data platforms
  • Proven track record of designing and implementing production-grade data pipelines
  • Strong problem-solving skills and attention to detail

Education

  • Bachelor's Degree in Computer Science, Engineering, Mathematics or related field OR
  • Related Field or Professional experience

Why Join Us?

  • Work with cutting-edge data engineering technologies
  • Collaborate with a talented and innovative team
  • Opportunity to build impactful data solutions at scale
  • Professional growth and continuous learning opportunities
  • Competitive compensation and benefits package
Similar roles

Keep a backup shortlist.

Browse stack
FocusData EngineeringRole area
Seniority signalSeniorCandidate level
StackAWS, Azure, CI/CDPrimary skills
Location1 accepted countryEligibility

Stack

Use these tags to compare similar remote roles.

Location eligibility

Candidates should apply only when their profile country is listed here.

Your profileCountry not setSign in to check your country against this role.

Hiring flow

WithMira shows the role, then sends candidates to the company application.

1Check role fit, stack, and location eligibility in WithMira.
2Open the company application page from the tracked apply link.
3Save the role or subscribe for similar opportunities before leaving.
Apply on company siteCompany siteOpen link