Senior Data Engineer

	 	 
Job Title: Senior Data Engineer
Location: Muharrem Fejza, Pristina (On-site)
Working Hours: 15:00 - 23:00 (local time)
LS Global specializes in optimizing business operations worldwide through expert outsourcing. We are currently recruiting for one of our clients for a Senior Data Engineer position. As a Senior Data Engineer, you will own the data platform powering the marketing engine. You’ll design batch and streaming frameworks, model complex systems into scalable schemas, and partner across teams to transform raw events into high-value data. This role is essential for driving confident, data-driven decisions through reliable and performant infrastructure at scale.
Key Responsibilities:

Design, build, and operate scalable, resilient batch and streaming data pipelines that power campaign analytics, attribution, and experimentation at scale.
Architect a common, reusable pipeline framework for both streaming and batch processing that engineering teams across the organization can adopt and build on.
Model real-world advertising systems — advertiser, campaign, offer, placement, and event data — into clean, scalable, and extensible data entities and schemas.
Own schema evolution, slowly changing dimensions, and historical state so datasets stay reliable and correct as downstream usage grows.
Write production-grade Python for data transformation, joins, aggregation, and reusable pipeline components, with a strong testing and validation mindset.
Orchestrate pipelines in Airflow/Dagster — owning DAG design, dependency management, idempotency, retries, backfills, and lineage.
Define and enforce data SLAs/SLOs, and build the schema checks, validation, and anomaly detection that catch issues before consumers do.
Instrument pipelines with monitoring and alerting (e.g., Datadog) and drive the team toward a proactive, guardrail-first data-quality posture.
Optimize for performance and cost at scale through partitioning, columnar/lakehouse storage formats (Parquet/Delta), and shuffle/skew-aware processing.
Partner with Account Managers, Operations, and Data Science to productionize the datasets and features that drive ad personalization, budget pacing, and bid optimization.
Mentor engineers and contribute to a culture of clean, maintainable, and well-documented data engineering.
Drive technical planning and contribute to the long-term evolution of the data architecture and platform strategy.

Requirements:

 Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. 
 5+ years of professional experience building and operating production-grade data pipelines. 
Production-level fluency in Python and strong SQL. 
 Deep data modeling and system-design ability: entities, relationships, cardinality, normalization, and slowly changing dimensions. 
 Hands-on experience with both streaming and batch processing, and the judgment to know when each is the right choice. 
 Strong grasp of distributed systems and performance — partitioning, shuffle/skew, fault tolerance, and columnar storage formats. 
 Experience with workflow orchestration (Airflow, Dagster, or equivalent) and a cloud data warehouse (BigQuery, Snowflake, or equivalent). 
 A data-reliability mindset: schema checks, anomaly detection, SLAs/SLOs, and observability built in from the start. 
 Comfort with ambiguity and a track record of making sound, defensible engineering tradeoffs with incomplete information. 

 Excellent communication and collaboration skills; able to work effectively with cross-functional teams across product, data, and business. 
Nice to Have / Bonus Qualifications

Master's degree in Computer Science, Engineering, or a related technical field.
Experience in the AdTech industry, especially with ad serving, real-time bidding, or campaign analytics and attribution.
Familiarity with cloud-native data development on Google Cloud Platform (GCP), particularly BigQuery.
Experience designing a shared or self-serve data platform / pipeline framework used by multiple teams.
Hands-on experience with data streaming and CDC technologies like Apache Kafka, Pub/Sub, Kinesis, or Flink.
Experience with lakehouse table formats (Delta, Iceberg, Hudi) and large-scale performance and cost tuning.
Familiarity with distributed processing engines such as Spark or Flink.
Exposure to data observability tooling and formal data-quality frameworks.
Familiarity with AI/ML data workflows, feature pipelines, A/B testing, or campaign experimentation systems.
Awareness of user privacy regulations relevant to advertising data (e.g., GDPR, CCPA, TCPA).

What We Offer:

Competitive salary based on experience.
Opportunities for professional growth and career advancement.
A collaborative and supportive work environment.
The opportunity to work with a U.S.-based client to build, scale, and optimize high-performance data pipelines and architecture, driving critical business insights.

Join our team as a Senior Data Engineer and support compliance initiatives, regulatory requirements, documentation reviews, and global operations through effective analysis, coordination, and cross-functional collaboration.