FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Senior Data Engineer
GFT Technologies. Design, build, and maintain scalable, resilient, and high-performance data pipelines.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and maintaining scalable data pipelines, ensuring data quality and governance, and collaborating across teams to modernize data platforms. Proficient in utilizing advanced data engineering tools and technologies to optimize data processing workflows.
Highest-signal resume keywords
Data EngineeringApache SparkAWS ServicesData ModelingETL and ELT Processes
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Pipeline DevelopmentScalaBatch and Streaming Data ProcessingData Quality Best PracticesSQL ServerNoSQL DatabasesGit-based Version ControlObservabilityData GovernanceData Transformation
Soft Skills
CollaborationProblem SolvingCommunication
Tools & Technologies
Apache KafkaAmazon MSKDelta LakeApache HudiApache IcebergDbtAirflowTerraformGlueRedshift
Industry Keywords
Distributed EnvironmentsHigh-Volume DataData ArchitectureLegacy System ModernizationLakehouse Architectures
Tech Stack
Tools & technologiesAirflowAmazon RedshiftApacheAWSETLKafkaNoSQLScalaSparkSQLTerraform
About the role
Key responsibilities & impact- Design, build, and maintain scalable, resilient, and high-performance data pipelines.
- Work with large volumes of structured and unstructured data.
- Ensure data quality, consistency, and governance throughout the information lifecycle.
- Develop processes for data ingestion, transformation, and delivery.
- Collaborate with software engineering, data analytics, data science, and business teams.
- Participate in defining data architectures and evaluating new technologies and tools.
- Monitor and optimize data processing workflows in distributed environments.
- Support initiatives to modernize and evolve the data platform.
Requirements
What you’ll need- Extensive experience in Data Engineering within distributed environments.
- Extensive experience with Apache Spark.
- Advanced knowledge of Scala.
- Experience with AWS services, including Glue, S3, EMR, Athena, and Redshift.
- Extensive experience with data modeling.
- Experience with ETL and ELT processes.
- Experience building data pipelines.
- Familiarity with relational databases.
- Familiarity with NoSQL databases and knowledge of SQL Server.
- Experience with batch and streaming data processing.
- Knowledge of data quality, security, and governance best practices.
- Experience with Git-based version control.
- Knowledge of observability and data pipeline monitoring.
- Preferred qualifications: experience with Apache Kafka or Amazon MSK; knowledge of legacy system modernization; experience with Delta Lake, Apache Hudi, or Apache Iceberg; familiarity with dbt, Airflow, and Terraform; experience with Lakehouse architectures; experience working in high-volume data environments.
Benefits
Comp & perks- Flexible benefits card – choose how and where to use it.
- Tuition assistance for undergraduate, graduate, MBA, and language courses.
- Certification incentive programs.
- Flexible working hours.
- Competitive salaries.
- Annual performance review with a structured career development plan.
- International career opportunities.
- Wellhub and TotalPass.
- Private pension plan.
- Childcare assistance.
- Health insurance.
- Dental insurance.
- Life insurance.