Data Engineer

24 hours ago


India SkillsCapital Full time

We are hiring multiple Data Engineers to join international data platform, analytics, and cloud engineering teams. These fully remote, long-term freelance roles are ideal for engineers who can build scalable data pipelines, work with modern cloud-native data stacks, and support large-scale enterprise data initiatives. Open Roles (Multiple Positions) We are recruiting across core and specialized data engineering areas: Core Data Engineering - Data Engineer - Senior Data Engineer - Cloud Data Engineer (AWS / Azure / GCP) Specialized Roles - ETL / ELT Developer - Big Data Engineer (Spark / Hadoop / Databricks) - Data Pipeline Engineer - Data Platform Engineer - Streaming Data Engineer (Kafka / Kinesis / Pub/Sub) If you have strong experience building data systems or pipelines, we encourage you to apply. Engagement Details - Type: Independent Freelance Consultant - Location: 100% Remote - Duration: Initial 6–12 month contract (extendable to multi-year) - Start Date: Immediate or within the next few weeks - Clients: Global enterprises, SaaS companies, and cloud-first data teams Key Responsibilities - Design and build scalable, reliable data pipelines using modern data engineering tools and frameworks. - Develop ETL/ELT workflows for structured, semi-structured, and unstructured data. - Implement data ingestion, transformation, storage, and processing solutions. - Work with cloud-native data services (AWS Glue, Redshift, EMR, Azure Data Factory, Synapse, GCP BigQuery, Dataflow). - Build batch and streaming data pipelines using Spark, Databricks, Kafka, or similar technologies. - Optimize performance, cost, and reliability of data systems for large-scale deployments. - Collaborate with analytics, BI, ML, and backend teams to deliver end-to-end data solutions. - Ensure data quality, integrity, governance, and security across data workflows. - Support CI/CD pipelines, version control, and automation related to data environments. Minimum Qualifications - Minimum 2 years of hands-on experience as a Data Engineer. - Strong experience with Python or SQL (or both). - Practical knowledge of data pipeline development using Spark, PySpark, or equivalent. - Hands-on experience with one major cloud platform (AWS, Azure, or GCP). - Understanding of data modeling, warehousing concepts, and distributed systems. - Experience working with ETL/ELT tools or frameworks. - Ability to work independently in a remote, distributed setup. Preferred Skills - Experience with Databricks or large-scale Spark clusters. - Knowledge of streaming technologies (Kafka / Kinesis / Pub/Sub / Flink). - Experience working with data lakes (S3, ADLS, GCS) and lakehouse architectures. - Exposure to orchestration tools such as Airflow, Dagster, Prefect, or AWS Step Functions. - Familiarity with containerization (Docker) and orchestration (Kubernetes). - Experience integrating with BI, ML, or analytics platforms. - Cloud certifications (AWS / Azure / GCP Data Engineer) are a plus. Why Join This Opportunity - Large-scale, cloud-native data engineering projects. - Multiple openings with fast-track onboarding. - Fully remote with flexible working hours. - Long-term freelance roles with consistent project work. - Work with modern data stacks, lakehouse architectures, and global teams. How to Apply Send your CV to Careers@SkillsCapital.io


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