id int64 | market string | country string | company string | role string | location string | sql int64 | python int64 | gcp int64 | aws int64 | azure int64 | bigquery int64 | dataflow int64 | pubsub int64 | airflow int64 | dbt_dataform int64 | spark int64 | kafka int64 | snowflake int64 | databricks int64 | docker_k8s int64 | terraform_iac int64 | ci_cd int64 | ai_llm int64 | data_modeling int64 | etl_elt int64 | governance_quality int64 | bi int64 | semantic_layer int64 | lakehouse_iceberg int64 | source_url string | checked_date string | source_note string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | TR | TΓΌrkiye | OREDATA | Data Engineer & Analytics Engineer (BigQuery & GA4 Expertise) | Δ°stanbul, TΓΌrkiye | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | https://tr.linkedin.com/jobs/view/data-engineer-analytics-engineer-bigquery-ga4-expertise-at-oredata-4082844145 | 2026-08-30 | BigQuery, DataForm/dbt, Composer/Airflow, DataFlow, BI tools and DWH explicitly listed. |
2 | TR | TΓΌrkiye | RoofStacks | Senior Data Engineer | Δ°stanbul, TΓΌrkiye | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | https://tr.linkedin.com/jobs/view/senior-data-engineer-at-roofstacks-4239359231 | 2026-08-30 | GCP, BigQuery, dbt/Dataform, Airflow, SQL, Python, dimensional modeling, Pub/Sub, governance and ETL/ELT. |
3 | TR | TΓΌrkiye | LC Waikiki | Analytics Engineer | Δ°stanbul, TΓΌrkiye | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | https://tr.linkedin.com/jobs/view/analytics-engineer-at-lc-waikiki-4448780599 | 2026-08-30 | BigQuery, dbt/Dataform, LLM APIs, embeddings/vector search/RAG, Azure AI Foundry or Vertex AI, Airflow/Composer and CI/CD. |
4 | TR | TΓΌrkiye | Aras Kargo | Data Engineer | Δ°stanbul, TΓΌrkiye | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | https://tr.linkedin.com/jobs/view/data-engineer-at-aras-kargo-4399315775 | 2026-08-30 | Python, SQL, Spark/Databricks/Flink, Airflow, AWS/Azure/GCP, DWH, dimensional modeling, ETL/ELT, CI/CD/IaC, LLM/RAG, streaming and governance. |
5 | TR | TΓΌrkiye | LC Waikiki | Data Engineer | Δ°stanbul, TΓΌrkiye | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | https://tr.linkedin.com/jobs/view/data-engineer-at-lc-waikiki-4419241121 | 2026-08-30 | Snowflake/Databricks/BigQuery, Airflow/Dagster/dbt, data modeling, data quality/governance, Docker/Kubernetes, Terraform, CI/CD and agentic AI. |
6 | TR | TΓΌrkiye | TikTak | Data Engineer | Δ°stanbul, TΓΌrkiye | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | https://tr.linkedin.com/jobs/view/data-engineer-at-tiktak-4437393050 | 2026-08-30 | Deep SQL/Python, dbt, Airflow, AWS S3/Redshift/Glue/Lambda, semantic/metrics layer, data modeling, governance, CI/CD and self-service BI. |
7 | TR | TΓΌrkiye | Dataroid | Data Engineer | Δ°stanbul, TΓΌrkiye | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | https://tr.linkedin.com/jobs/view/data-engineer-at-dataroid-4141624182 | 2026-08-30 | Python/Java, Spark/Flink/Kafka Streams, Airflow/dbt, Git, Iceberg/Delta Lake, Docker/Kubernetes and S3 listed. |
8 | TR | TΓΌrkiye | EPAM Systems | Senior Data Engineer with Terraform | TΓΌrkiye | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | https://tr.linkedin.com/jobs/view/senior-data-engineer-with-terraform-at-epam-systems-4457225723 | 2026-08-30 | SQL, Python, GCP, BigQuery, Dataflow, Dataform/dbt, Composer/Airflow, Pub/Sub, Terraform, GitHub Actions, data quality, Iceberg and Looker. |
9 | TR | TΓΌrkiye | Trendyol Group | Data Engineer | Δ°stanbul, TΓΌrkiye | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | https://tr.linkedin.com/jobs/view/data-engineer-at-trendyol-group-4320059628 | 2026-08-30 | SQL, Python nice-to-have, Spark/Flink, Kafka, GCP/BigQuery, Snowflake, Iceberg/Delta Lake, Airflow, Docker/Kubernetes, Terraform, CI/CD and data quality. |
10 | TR | TΓΌrkiye | OBSS | Data Engineer | Δ°stanbul, TΓΌrkiye | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | https://tr.linkedin.com/jobs/view/data-engineer-at-obss-4388328752 | 2026-08-30 | Python, SQL, Spark, Kafka, Airflow, AWS/Azure/GCP, Docker/Kubernetes, Terraform, CI/CD, DataOps/MLOps and AI-powered tools. |
11 | Global | United States | Pivotal Solutions | Senior Data Engineer (Python, dbt & Snowflake) - Remote | United States (Remote) | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | https://www.linkedin.com/jobs/view/senior-data-engineer-python-dbt-snowflake-remote-at-pivotal-solutions-4449873955 | 2026-08-30 | Strong SQL/Python, dbt, Snowflake, Airflow, Git/CI/CD; migration/refactor, tests and documentation emphasized. |
12 | Global | United States | RYZE | Analytics Engineer | United States | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | https://www.linkedin.com/jobs/view/analytics-engineer-at-ryze-4451872208 | 2026-08-30 | Production SQL, dbt models in Snowflake, Fivetran connectors, warehouse hygiene, testing and Sigma dashboards. |
13 | Global | United States | Capgemini | Snowflake Data Engineer (DBT) | New York, United States | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | https://www.linkedin.com/jobs/view/snowflake-data-engineer-dbt-at-capgemini-4431402609 | 2026-08-30 | Snowflake, dbt, advanced SQL, Python, ETL/ELT, Airflow/Prefect, cloud platforms, dimensional modeling, governance, CI/CD and BI. |
14 | Global | United States | First Citizens Bank | Lead Data Engineer | California, United States | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | https://www.linkedin.com/jobs/view/lead-data-engineer-at-first-citizens-bank-4438144111 | 2026-08-30 | Snowflake/dbt, SQL, Python, Airflow/Astronomer, ETL/ELT, DWH/dimensional modeling, governance, CI/CD and AI productivity tools. |
15 | Global | United States | Ncontracts | Analytics Engineer | United States | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | https://www.linkedin.com/jobs/view/analytics-engineer-at-ncontracts-4387272073 | 2026-08-30 | SQL, dbt, Snowflake (BigQuery/Redshift/Databricks comparable), dimensional modeling, BI, governance/data contracts, CI/CD, orchestration and AI curiosity. |
16 | Global | Spain | GFT Technologies EspaΓ±a | Data Engineer | Madrid, Spain | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | https://es.linkedin.com/jobs/view/data-engineer-at-gft-technologies-espa%C3%B1a-4459675944 | 2026-08-30 | Python, Spark, Kafka, advanced SQL, AWS/Azure, Airflow/dbt, ETL/ELT, data modeling, governance and Delta Lake/Data Lake. |
17 | Global | Germany | INTERSPORT Digital GmbH | Data Engineer β Data Plattform | Germany | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | https://de.linkedin.com/jobs/view/data-engineer-%E2%80%93-data-plattform-m-w-d-at-intersport-digital-gmbh-4429674225 | 2026-08-30 | SQL, Python, Snowflake, dbt, Prefect/Airflow, BigQuery, ETL/ELT, data modeling, AWS, Terraform, BI, Kafka/Spark and governance. |
18 | Global | Germany | Theo | Lead Data Engineer | Berlin, Germany | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | https://de.linkedin.com/jobs/view/lead-data-engineer-w-m-d-at-theo-4443391515 | 2026-08-30 | SQL, Python, dbt, BigQuery, Airflow/Composer, GCP, CI/CD/observability, AI-assisted tools and data layers designed for agents/automation. |
19 | Global | Germany | FUNKE | Data Engineer | Berlin, Germany | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | https://de.linkedin.com/jobs/view/data-engineer-m-w-d-at-funke-4437425913 | 2026-08-30 | Airflow, Beam, BigQuery, dbt, Docker, GCP, Pub/Sub, Cloud Run/SQL, Terraform, Python and SQL. |
20 | Global | Netherlands | idpp | Data Engineer | Randstad, Netherlands | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | https://nl.linkedin.com/jobs/view/data-engineer-at-idpp-4456915451 | 2026-08-30 | GCP, BigQuery, GCS, Composer/Airflow, dbt, SQL, Python, DWH, dimensional modeling, CI/CD/Git and data quality. |
π Data Job Market Trends 2026
What if job postings were treated as a dataset rather than a list of requirements?
This dataset was created as part of my Week 4 self-learning study to explore which technical skills are explicitly mentioned in current data-related job postings.
π What's inside?
The dataset contains a small research sample of:
- πΉπ· 10 job postings from TΓΌrkiye
- π 10 global job postings
- 20 postings in total
Each posting was transformed into structured features such as:
- SQL
- Python
- GCP
- AWS
- Azure
- BigQuery
- Airflow
- dbt / Dataform
- Spark
- Kafka
- Snowflake
- Databricks
- Docker / Kubernetes
- Terraform / IaC
- CI/CD
- AI / LLM
- Data Modeling
- ETL / ELT
- Governance / Data Quality
- BI
- Semantic Layer
- Lakehouse / Iceberg
π§ How was it created?
For each job posting:
1 = the skill was explicitly mentioned0 = the skill was not explicitly mentioned
I intentionally avoided assuming that an unmentioned technology was unnecessary.
This makes the dataset a representation of explicit job-posting signals, rather than a complete measurement of the entire job market.
π¬ What did I do with it?
I uploaded the dataset to Google BigQuery and used SQL to investigate questions such as:
- Which skills appear most frequently?
- How do TΓΌrkiye and global postings differ?
- Which technologies form recurring skill clusters?
- Which skills might deserve priority in my learning roadmap?
One interesting pattern in my sample was the combination of:
SQL + Airflow + dbt/Dataform + Data Modeling + Governance
rather than any single technology standing alone.
β οΈ Limitations
This is a small, manually curated sample of 20 job postings.
It should not be interpreted as a statistically representative picture of the entire 2026 job market.
The goal is exploratory learning and trend discovery.
π Next Step
The next step of this project is to turn the dataset into an interactive Hugging Face Space where users can explore:
TΓΌrkiye πΉπ· vs Global π
skill demand and emerging data trends themselves.
Built as part of the Shining Stars β Week 4 Self-Learning Study.
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