Location: Muharrem Fejza, Pristina (On-site)
Working Hours: 15:00 - 23:00 (local time)
LS Global focuses on improving business operations globally through specialized outsourcing services. The company is hiring on behalf of one of its clients for the role of Senior Data Engineer. In this position, you will take ownership of the data platform that supports the marketing engine. The role involves creating batch and streaming frameworks, translating complex systems into scalable schemas, and working closely with different teams to turn raw events into valuable data. This position plays a key role in enabling confident, data-driven decision-making through dependable and high-performing infrastructure at scale.
Key Responsibilities:
- Develop, implement, and manage scalable and reliable batch and streaming data pipelines that support campaign analytics, attribution, and experimentation at scale.
- Create a shared and reusable pipeline framework for both streaming and batch workloads that engineering teams across the organization can use and extend.
- Structure real-world advertising systems — advertiser, campaign, offer, placement, and event data — into clear, scalable, and extensible data entities and schemas.
- Manage schema evolution, slowly changing dimensions, and historical state to ensure datasets remain accurate and dependable as downstream usage expands.
- Produce production-grade Python code for data transformation, joins, aggregation, and reusable pipeline components, with strong attention to testing and validation.
- Coordinate pipelines in Airflow/Dagster, including DAG design, dependency handling, idempotency, retries, backfills, and lineage.
- Establish and uphold data SLAs/SLOs, while building schema checks, validation processes, and anomaly detection to identify problems before they affect users.
- Equip pipelines with monitoring and alerting tools such as Datadog and help guide the team toward a proactive, guardrail-first approach to data quality.
- Improve performance and cost efficiency at scale through partitioning, columnar/lakehouse storage formats such as Parquet/Delta, and shuffle/skew-aware processing.
- Collaborate with Account Managers, Operations, and Data Science to productionize datasets and features that support ad personalization, budget pacing, and bid optimization.
- Support and mentor engineers while helping maintain a culture centered on clean, maintainable, and well-documented data engineering practices.
- Contribute to technical planning and support the long-term development 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.
- Strong ability in data modeling and system design, including entities, relationships, cardinality, normalization, and slowly changing dimensions.
- Practical experience with both streaming and batch processing, along with the judgment to determine when each approach is appropriate.
- Solid understanding of distributed systems and performance topics, including partitioning, shuffle/skew, fault tolerance, and columnar storage formats.
- Experience with workflow orchestration tools such as Airflow, Dagster, or equivalent, as well as a cloud data warehouse like BigQuery, Snowflake, or equivalent.
- A data reliability mindset, including schema checks, anomaly detection, SLAs/SLOs, and observability integrated from the beginning.
- Ability to work comfortably in ambiguous situations and a proven record of making sound and defensible engineering tradeoffs with incomplete information.
Excellent communication and collaboration abilities, with the capacity to work effectively across cross-functional teams spanning 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 in 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 or pipeline framework used by multiple teams.
- Hands-on experience with data streaming and CDC technologies such as Apache Kafka, Pub/Sub, Kinesis, or Flink.
- Experience with lakehouse table formats including Delta, Iceberg, and Hudi, as well as large-scale performance and cost optimization.
- 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, such as GDPR, CCPA, and TCPA.
What We Offer:
- A competitive salary determined by experience.
- Opportunities for professional development and career progression.
- A collaborative and supportive workplace environment.
- The chance to work with a U.S.-based client on building, scaling, and optimizing high-performance data pipelines and architecture that enable critical business insights.
Join the team as a Senior Data Engineer and contribute to global operations through effective analysis, coordination, and collaboration across teams.
