inDrive

19 hours ago

Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Build and operate batch and streaming ingestion into a layered BigQuery data warehouse for analytics, machine learning, and streaming/CDC delivery. Integrate marketing, payments, S3, and third-party APIs end-to-end, engineer the data platform in Python, and implement reliability and correctness practices (idempotency, deduplication, replay, monitoring). Drive data governance using BigQuery/IAM/PII controls and Databricks Unity Catalog, and create internal tools for agentic workflows.

Location: Almaty

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Build and operate batch and streaming ingestion into a layered BigQuery DWH (raw → ODS → data marts) using Airflow, Debezium CDC over Kafka with protobuf, Pub/Sub, and Dataflow.
•Integrate external data sources end-to-end (marketing platforms, payment providers, S3 buckets, third-party APIs), including schema contracts, backfills, and reconciliation.
•Engineer the data platform in Python by creating custom Airflow operators and connectors, running Kafka Connect on Strimzi (K8s), and building Cloud Functions and API integrations.
•Implement BigQuery CI/CD and change-management tooling using GitHub-based test-and-approval flows and SQL migration engines (Liquibase/Flyway/Bytebase) with sandbox validation plus backup and rollback.
•Ensure pipeline reliability and correctness (idempotency, deduplication, late-data handling, backfill/replay, freshness monitoring/alerting) and write integration/unit tests.

Pay and Benefits

Perks:Learning Budget

Key Requirements

•Strong practical Python experience building clean, well-structured, and tested services and data pipelines.
•Experience building and operating services in a cloud environment (GCP, AWS or similar), including CI/CD, containerization, and monitoring/alerting.
•Hands-on experience with DWH tasks (BigQuery or a cloud warehouse) and confident SQL skills.
•Familiarity with Kubernetes and Terraform in a GCP/K8s-based infrastructure.
•Ability to communicate clearly with non-engineering stakeholders and support data requests from analysts and business teams.

Experience:Data engineeringAnalyticsMachine learningStreaming dataData warehouse

Skills:CommunicationOwnershipProactive problem solving

Tech Stack:PythonGCPAWSBigQueryDatabricksKubernetesK8sAirflowDebeziumKafkaProtobufPub/SubDataflowTerraformStrimziCloud FunctionsGitHubLiquibaseFlywayBytebase

Company Brief

inDrive

A ride-hailing and mobility platform that lets passengers and drivers negotiate fares directly in real time. It also offers intercity travel, courier, and delivery services in multiple countries.

Industry: Mobility Platforms

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Mountain View, United States

Founded: 2013

Website LinkedIn

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inDrive

19 hours ago

Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Location: Almaty

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Build and operate batch and streaming ingestion into a layered BigQuery DWH (raw → ODS → data marts) using Airflow, Debezium CDC over Kafka with protobuf, Pub/Sub, and Dataflow.
•Integrate external data sources end-to-end (marketing platforms, payment providers, S3 buckets, third-party APIs), including schema contracts, backfills, and reconciliation.
•Engineer the data platform in Python by creating custom Airflow operators and connectors, running Kafka Connect on Strimzi (K8s), and building Cloud Functions and API integrations.
•Implement BigQuery CI/CD and change-management tooling using GitHub-based test-and-approval flows and SQL migration engines (Liquibase/Flyway/Bytebase) with sandbox validation plus backup and rollback.
•Ensure pipeline reliability and correctness (idempotency, deduplication, late-data handling, backfill/replay, freshness monitoring/alerting) and write integration/unit tests.

Pay and Benefits

Perks:Learning Budget

Key Requirements

•Strong practical Python experience building clean, well-structured, and tested services and data pipelines.
•Experience building and operating services in a cloud environment (GCP, AWS or similar), including CI/CD, containerization, and monitoring/alerting.
•Hands-on experience with DWH tasks (BigQuery or a cloud warehouse) and confident SQL skills.
•Familiarity with Kubernetes and Terraform in a GCP/K8s-based infrastructure.
•Ability to communicate clearly with non-engineering stakeholders and support data requests from analysts and business teams.

Experience:Data engineeringAnalyticsMachine learningStreaming dataData warehouse

Skills:CommunicationOwnershipProactive problem solving

Tech Stack:PythonGCPAWSBigQueryDatabricksKubernetesK8sAirflowDebeziumKafkaProtobufPub/SubDataflowTerraformStrimziCloud FunctionsGitHubLiquibaseFlywayBytebase

Company Brief

inDrive

A ride-hailing and mobility platform that lets passengers and drivers negotiate fares directly in real time. It also offers intercity travel, courier, and delivery services in multiple countries.

Industry: Mobility Platforms

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Mountain View, United States

Founded: 2013

Website LinkedIn