See the top technical and behavioral skills and phrases desired by employers.
Technical Skills/Phrases
Core technical skills and phrases employers request most often.
Write and tune complex SQL transformations while preserving correct joins, aggregations, and business meaningDesign relational and dimensional data models with explicit grain, keys, relationships, and historical changesBuild incremental batch ingestion and transformation pipelines from operational systems, files, and APIsImplement streaming pipelines that address ordering, late events, duplicates, and replayOrchestrate dependencies, schedules, retries, backfills, and recovery across data workflowsOptimize distributed processing through partitioning, resource sizing, and investigation of skew and shufflesDesign warehouse and lakehouse storage layouts for reliable loading and efficient downstream accessIntegrate cloud data services according to workload, access, availability, and cost requirementsDevelop maintainable pipeline components with tested Python code and role-appropriate JVM languagesValidate data with reconciliation, automated quality checks, and actionable handling of failed recordsInstrument freshness, completeness, latency, lineage, and operational alerts for data productsEngineer repeatable processing and recovery with idempotent writes and documented failure handlingProtect sensitive datasets through least-privilege access, secure credentials, and appropriate data controlsImplement metadata ownership, data contracts, schema compatibility, and lifecycle governanceVersion and deploy pipeline code and data changes through review, automated testing, and controlled releasesReduce compute and storage cost without breaking data correctness or delivery commitmentsTranslate domain entities, business rules, and consumer needs into usable, documented data productsEvaluate AI-assisted data code and operational recommendations with tests, provenance, and human review
Behavioral Skills/Phrases
Professional skills and phrases that help candidates collaborate, communicate, and grow into senior roles.
Turn ambiguous stakeholder requests into agreed deliverables and acceptance criteriaExplain data limitations and engineering tradeoffs to nontechnical decision-makersCoordinate handoffs between source owners, platform teams, and downstream consumersEscalate blockers and uncertain assumptions early with realistic optionsLead constructive incident discussions focused on impact, evidence, and preventionNegotiate delivery scope when freshness, quality, cost, and deadlines conflictDocument decisions and ownership so another engineer can operate the systemGive useful feedback in reviews without hiding unresolved technical disagreementsMake competing requests and their business priorities visible to the teamValidate domain assumptions with the people who understand the underlying business processExercise professional restraint when handling confidential or misleading dataLearn unfamiliar platforms through focused experiments and feedback rather than unsupported claimsBusiness acumenCritical thinkingAttention to detailCustomer focusAutonomyDependabilityAdaptabilityResourcefulnessMentoringInfluenceResilienceTeamwork
