Senior Data Engineer

🔥 0 minutes ago

🇭🇺 Hungary – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Dynata

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

💼 Consulting

📣 Marketing

☁️ SaaS

💰 $31.5M Debt Financing - Dynata on 2024-05

Consulting • Marketing • SaaS

Dynata is a market research and data company that provides high-quality first-party survey panels, audience data, and a suite of survey and analytics platforms to help organizations collect, activate, and measure insights. The company offers global B2B and B2C panels, survey scripting and fielding tools, data enrichment, audience activation, brand lift measurement, and data visualization, and it emphasizes data quality using AI/ML (QualityScore™) and security certifications. Dynata serves researchers, brands, media agencies, publishers, pollsters, and academics with both self-service and managed services.

📋 Description

• Design and implement scalable batch and streaming data pipelines using Apache Spark, Kafka, and Flink • Build and maintain Bronze/Silver/Gold medallion architecture within the lakehouse using Delta Lake or Iceberg • Develop and optimize complex SQL and PySpark transformations for large-scale datasets • Integrate structured, semi-structured, and unstructured data sources into the lakehouse • Collaborate with data architects to evolve physical and logical data models • Implement data quality checks and monitoring using Great Expectations or dbt tests • Write Infrastructure-as-Code for pipeline environments using Terraform and Helm • Participate in code reviews and enforce engineering standards and best practices • Troubleshoot pipeline failures, performance bottlenecks, and data incidents • Mentor junior and mid-level data engineers and contribute to internal knowledge sharing

🎯 Requirements

• 6+ years of data engineering experience with a track record of enterprise-scale delivery • Expert proficiency in Python and SQL • PySpark experience required • Hands-on experience with Apache Spark, Delta Lake, or Apache Iceberg • Experience with Apache Airflow, Prefect, or Dagster • Strong knowledge of AWS Glue, Azure Data Factory, or GCP Dataflow • Proficiency with Git, CI/CD pipelines, Docker, and Kubernetes • Experience with dbt (data build tool) • Bachelor's degree in Computer Science, Engineering, or related technical field

🏖️ Benefits

• Inclusive, accessible work environment • Accommodations by request for all aspects of the selection process