Data Engineer – Snowflake, Databricks, BigQuery

Job not on LinkedIn

🔥 3 minutes ago

🇮🇳 India – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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FyerX - Your Trusted Marketing Partner

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

📣 Marketing

🤝 B2B

Marketing • B2B

FyerX is a marketing agency based in Bangalore that specializes in helping businesses enhance their digital presence and improve online outcomes through tailored marketing strategies. With a passionate team of marketing experts, FyerX focuses on various aspects of digital marketing including social media marketing, branding, search engine optimization, and influencer marketing. They aim to fuel the growth of purpose-driven brands by developing integrated marketing plans that drive online growth and improve brand visibility.

📋 Description

• Design and engineer highly scalable data ingestion pipelines for structured, semi-structured, and unstructured data from APIs, databases, and application logs • Develop complex ELT/ETL transformation models using Python, SQL, dbt, Apache Spark, and PySpark • Architect and optimize enterprise cloud data platforms in Snowflake, Databricks, or BigQuery • Design optimized schemas, clustering keys, partition strategies, and storage parameters • Implement automated data orchestration pipelines with workflow schedules, error-handling paths, and dependency graphs using Apache Airflow, Prefect, or Mage • Establish data quality and validation gates • Monitor data latency, validate structural constraints, check row balances, and enforce data anomaly alerts • Optimize query performance and cluster costs • Audit resource utilization, restructure inefficient SQL joins, manage micro-partitioning schemas, and tune execution bottlenecks • Govern data platform access and compliance layers • Configure row- and column-level security, data masking rules, and RBAC access control policies

🎯 Requirements

• 4 to 8 years of core database engineering or backend development experience • 3+ dedicated years actively building and maintaining enterprise-scale data infrastructure footprints • 3+ years of dedicated data engineering experience designing pipelines and analytics data warehouses • Mandatory certification: Snowflake Certified Core Data Engineer, Databricks Certified Data Engineer Professional, or Google Cloud Certified Professional Data Engineer • Strong technical mastery of advanced SQL optimization • Python programming proficiency • Experience with relational/dimensional data modeling, including Star/Snowflake schemas and Data Vault • Experience with cloud storage setups • Deep understanding of distributed computing principles • Understanding of big data architectures • Understanding of data stream processing constraints • Understanding of cloud resource pricing structures • Prior experience managing large-scale legacy data warehouse migrations over to modern cloud data lakes is preferred • Familiarity with streaming architectures using Apache Kafka, Flink, AWS Kinesis, Google Pub/Sub, or similar cloud-native event systems is preferred

🏖️ Benefits

• Remote work arrangement • Contract employment