Data Engineering Manager

Unifonic

Operating and evolve a large volume data lake and streaming pipelines with clear SLOs for latency, freshness, completeness, and accuracy. Establish on-call, runbooks, and incident response for data platform reliability .

Implementing data quality by design: data modeling/contracts, schema governance, and automated validation embedded in data pipelines and orchestration (Airflow/Dagster) .

Delivering high-accuracy reporting and certified metrics with a governed semantic layer, ensure consistent definitions across C-level dashboards and customer-facing APIs .

Building and optimize streaming use cases (Kafka + Spark/Flink) with exactly-once semantics, late-data handling, CDC, backfill strategies, set and meet near-real-time SLAs for dashboards .

Owning real-time OLAP serving: design and operate Vertica/ClickHouse tables, partitioning, indexing, projections/rollups, and retention to balance latency, cost, and concurrency .

Establishing end-to-end observability (metrics, logs, traces, lineage) across dataflows and APIs; track MTTD/MTTR and error budgets for data incidents .

Optimizing cost/performance across storage and compute (tiering, compression, query optimization, autoscaling) on OCI/AWS/GCP.

Shipping robust, versioned analytical APIs (batch/streaming) with SLAs, schema governance, and usage monitoring.

Coaching and grow high-performing teams, and communicate status and trade-offs clearly to executives and non-technical stakeholders.